Predictors of late initiation of breastfeeding practice in Ethiopia: a multilevel mixed-effects analysis of recent evidence from EDHS 2019

Abstract

Objectives

To identify the predictors of late initiation of breastfeeding practice in Ethiopia.

Design

Cross-sectional study design.

Setting

Ethiopia.

Participants

A total of 1982 weighted samples of mothers with children aged under 24 months were included.

Outcome measure

Late initiation of breastfeeding practice.

Results

The prevalence of late breastfeeding initiation practice is 26.4% (95 CI 24.4 to 28.3). Being a young mother (15–24 years) (adjusted odds ratio (AOR) =1.66; 95 CI 1.06 to 2.62), no antenatal care (ANC) visit (AOR=1.45; 95 CI 1.04 to 2.02), caesarean section (AOR=4.79; 95 CI 3.19 to 7.21) and home delivery (AOR=1.53; 95 CI 1.14 to 2.06) were found to be the determinants of late initiation of breast feeding.

Conclusion

More than one-fourth of newborn children do not start breast feeding within the WHO-recommended time (first hour). Programmes should focus on promoting the health facility birth and increasing the ANC visits. Further emphasis should be placed on young mothers and those who deliver via caesarean section to improve the timely initiation of breast feeding.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• This study uses nationally representative data, enabling generalisability at the country level and providing enhanced statistical power.

• The secondary nature of the data limits the exploration of additional predictors of late initiation of breastfeeding practices.

• Due to the cross-sectional nature of the data, establishing a causal relationship between the explanatory and outcome variables is challenging.

Introduction

The initial period after birth is among the riskiest times in a child’s life, but early breast feeding offers neonates a vital line of defence.¹ Breast feeding is the most efficient and significant method of ensuring a child’s well-being and continued survival. Breast milk is the most suitable food for babies.² It is the most preserved and healthy and comprises antibodies that prevent several diseases in children. It provides the infant with all the necessary energy and nutrition.³ Breast feeding results in fewer infections, increased intelligence, probable protection against overweight and diabetes, and serves as a preventive measure against cancer for mothers.⁴

Despite the significant recommendations from UNICEF and WHO to initiate breast feeding within the first hour after delivery, several neonates are not breast fed within the recommended time.⁵ The initiation of breast feeding within 1 hour of birth is crucial for safeguarding newborns from acquiring infections, thereby reducing newborn mortality. Additionally, it fosters emotional bonding with the mother and positively impacts the extent of exclusive breast feeding.⁶ Furthermore, this practice stimulates the production of breast milk. The yellowish first milk, known as colostrum, is produced on the first day, serving as a crucial source of nutrients and boosting the child’s immunity.⁷

Delayed initiation of breast feeding is linked to severe sepsis, a condition that heightens the risk of neonatal mortality.⁸ Additionally, it is linked to prelacteal feeding practices, which may increase the risk of hospitalisation, diarrhoea and lower respiratory tract infections.⁹ On-time breastfeeding initiation is also associated with a decreased chance of postpartum haemorrhage.¹⁰ Furthermore, timely breastfeeding initiation enhances maternal-infant bonding, significantly contributing to early child development.¹¹

Recent studies have shown that the risk of neonatal mortality increases by 33% among neonates who start breast feeding more than 1 hour after birth.^{12 13}

Worldwide, three out of every five neonates had late initiation of breast feeding. In 2017 alone, approximately 78 million newborn babies did not initiate breast feeding within 1 hour of birth.¹⁴ In low-income and middle-income regions, the prevalence of late breastfeeding initiation is 53.8%. It ranges from 15.0% in Burundi to 83.4% in Guinea.⁸

Despite the well-documented benefits of optimal breastfeeding practices in reducing malnutrition and child mortality, Ethiopia faces a significant challenge. 18.2% of children do not start breast feeding within the crucial first hour after birth, and only 47% are exclusively breast fed for the recommended 6 months.¹⁵ This inadequate child feeding has demonstrably negative consequences. Recent data revealed concerns about high neonatal, infant and under-5 mortality rates of 33, 47 and 59 deaths per 1000 live births, respectively.¹⁶ Furthermore, chronic malnutrition remains prevalent, with 23.1% of Ethiopian children classified as stunted.¹⁷ These findings indicate that current child-feeding practices in Ethiopia do not yet have a significant impact on overall child health. Therefore, identifying the key determinants of breastfeeding practices is of paramount importance. This knowledge will inform the targeted interventions aimed at improving child feeding practices, with the ultimate goal of reducing malnutrition and mortality rates among Ethiopian children.

Factors affecting the late initiation of breast feeding have been identified in different studies. These include maternal age,¹⁸ rural residence status,¹⁹ marital status,²⁰ place of birth,²¹ maternal educational level,²² modes of delivery,^23–25 media exposure,²⁶ maternal body mass index,²⁷ parity,^{28 29} counselling during antenatal care (ANC) appointment,^{30 31} frequency of ANC,³² poor wealth index,³³ births attended by skilled health personnel³⁴ and maternal knowledge of newborn danger signs.³⁵

By 2030, the Sustainable Development Goals aim to decrease newborn and under-five mortality to as low as 12 and 25 per 1000 live births, respectively.³⁶ In achieving the above plan, initiating breast feeding within 1 hour after birth and exclusively breast feeding for the first 6 months of a child’s life play a prominent role. Furthermore, the Ethiopia Health Sector Transformation Plan emphasises achieving optimal breastfeeding practices to reduce under-5 mortalities from 59 to 36 per 1000 live births.³⁷

Despite the significant progress made previously and the recognised health benefits of optimal breastfeeding practices, ending late initiation of breast feeding in low-income countries, such as Ethiopia, has become a considerable challenge. Most studies on breastfeeding practices in Ethiopia are limited to specific districts or areas.21 30 38–40 Furthermore, recent data on breastfeeding practice are crucial for public health practitioners and policymakers to support efforts towards improving child nutrition programmes and eliminating all forms of malnutrition in the later stages of children’s lives.

Furthermore, the study was carried out using recent data (2019) from the Ethiopia Demographic and Health Survey (EDHS), which is crucial for providing up-to-date information on national improvements in breastfeeding practices. Understanding the factors that determine the late initiation of breast feeding is essential for designing strategies to improve child nutrition. It also accelerates interventions towards breastfeeding practices. Thus, this study aimed to determine the predictors of late initiation of breastfeeding practices in Ethiopia.

Methods

Study setting, study period and data source

According to forecasts from Trading Economics and data from recent census figures, the total population of Ethiopia was 115.0 million by 2020.⁴¹ The EDHS 2019 final report includes comprehensive data at the country level from nine regional states and two municipal administrations. The administrative levels were divided into zones, woredas and so forth. A multilevel analysis was conducted on children <24 months old. Women between the ages of 15 and 49 and children in selected households across the country were the target groups. The EDHS collects pertinent information mainly regarding maternity healthcare utilisation, marriage and sexual behaviour, child feeding practices and children’s and women’s dietary conditions. Data collection was carried out from March to June.¹⁶

Data extraction and population

First, the project proposal was sent to the Demographic and Health Surveys (DHS) Programme. After a detailed review process, the DHS programme accepted the proposal and granted access to the survey datasets. Data extraction was performed to select mothers of children aged <24 months. The data extraction took place between 1 August 2023 and 30 August 2023. All Ethiopian mothers of children aged <24 months composed the source population, whereas those in the selected enumeration area composed the study population.

Sampling methods and design

The EDHS 2019 sample was stratified and selected at two levels. 21 sampling strata were produced by stratifying each region into urban and rural areas. Using probability proportions, 305 enumeration areas (93 from urban areas and 212 from rural areas) were selected in the first stage. A newly formed household listing was used in the second stage to choose a set number of 30 households per cluster with an equal probability of systematic selection. Sample allocation was performed to ensure that survey precision was equivalent across the regions. 35 enumeration areas were selected from the 3 largest regions, and 25 enumeration areas were selected from 8 regions (including 2 city administrations). The complete sampling procedure is available in the EDHS 2019 final report.⁴² A cross-sectional study was conducted among 1982 weighted mothers of children under 24 months of age who participated. The spotlight sampling technique for the present study is shown in the figure below (figure 1).

Figure 1.

Schematic representation of the sampling procedures in the study of predictors of late initiation of breast feeding in Ethiopia, Ethiopia Demographic and Health Survey, 2019. EAs, enumeration areas.

Study variables

The dependent variable in this study was the late initiation of breastfeeding practice. Various independent variables were considered to identify the determinants of late initiation of breast feeding (table 1). The community poverty level is constructed using individual-level factors at the cluster (community) level, classified as lower or higher by using the median value as a cut-off point if the distribution is not normal. Furthermore, the distribution was checked using a histogram.

Table 1.

List of independent variables for the assessment of predictors of late initiation of breast feeding in Ethiopia

Variables	Description (classification)
Mother age	15–24, 25–34, 35–49
Residence status	Urban or Rural
Religion	Orthodox, Protestant, Muslim, Other
Region	Larger central: Tigray, Amhara, Oromia, SNNPR Small peripherals: Benishangul, Gambella, Afar, Somali Metropolis: Harari, Addis Ababa, Dire Dawa67 68
Mother educational status	No education, primary, secondary or higher
Wealth index	Poor, middle,and rich
Marital status	Not married or married
Antenatal	No ANC visit, 1–3 or 4 and above
Place of delivery	Home or health institution
Mode of delivery	SVD or caesarean section
Type of birth	Single or twin and above
Sex of child	Male or female
Parity	1–2, 3–4 or 5 and above
Community poverty level	Higher or lower

ANC, antenatal care; SNNPR, Southern Nations, Nationalities, and Peoples' Region; SVD, spontaneous vaginal delivery.

Definitions

Late initiation of breast feeding is defined as the failure to initiate breast feeding within 1 hour after birth as recommended by the WHO.^{8 43} The outcome variable is dichotomised as ‘1’ if breast feeding is initiated after the first hour of birth or ‘0‘ if it is initiated within 1 hour.

Data processing and analysis

The data were extracted from the individual record folder of the EDHS 2019 using STATA V.17. Sorting and listing procedures were employed to identify any missing values. Descriptive statistics, including frequency and percentage, were computed. Data weighting, cleaning, editing and recording processes were conducted. The analysis was performed using STATA V.17.

Multilevel logistic regression analysis

Multilevel mixed-effect logistic regression analysis was conducted to identify the significant determinants of late initiation of breast feeding. Multilevel modelling is a statistical approach used to analyse data collected at different levels. The equation for the model can be expressed as Logit(π_ij) = β₀ + βx_ij + U_j; where β₀ represents intercepts, β represents individual-level factors (unknown) and U_j represents Gaussian random effects that are mutually independent.⁴⁴

A multilevel model was fitted due to the hierarchical nature of the EDHS data. Four models were considered. The first (null) model considers only the dependent variable to explore the degree of cluster variation in the late initiation of breast feeding. The second and third models include individual-level factors and community-level factors, respectively. The fourth model was adjusted for both the individual and community levels concurrently. Adjusted odds ratio (AOR) and their respective 95% CI were computed to identify significant predictors of late initiation of breast feeding. The variance inflation factor (VIF) and tolerance values were used to check for the existence of multicollinearity between variables. A VIF above 4 or a tolerance below 0.25 indicated that multicollinearity might exist.^{45 46} To estimate the variation between clusters, proportional change in variance (PCV), intraclass correlation (ICC) and median odds ratio (MOR) were computed.

ICC shows the degree of heterogeneity of late breastfeeding initiation between clusters and calculated as ${\displaystyle ICC=\frac{{\sigma }^2}{\left({\sigma }^2+{\sigma }_b^2\right)}}$, where σ² represents community level variance, ${\sigma }_b^2$ indicates individual level variance.⁴⁷ ${\sigma }_b^2=\frac{{\pi }^2}{3}$.

MOR is the median variation in the OR between high-risk areas of late breastfeeding initiation and low-risk areas during random selection of clusters. It is calculated as

${\displaystyle \mathrm{M}\mathrm{O}\mathrm{R}=e^{\left[\sqrt{\left(2\times V_A\right)0.6745}\right]}=e^{\left[0.95\times {\sqrt{V}}_A\right]}}$, where V_A represents the area level variance.⁴⁸

PCV measures the total variation in the late initiation of breast feeding attributable to factors in successive models. It is computed as ${\displaystyle PCV=\frac{V\text{null}-VA}{V\text{null}}\times 100\mathbf{\%}}$, where V_null is the variance in the null model and V_A is the variance in the successive model.⁴⁹

Patient and public involvement

Patients and/or the public were not involved in the design, conduct, reporting or dissemination of this research.

Results

Sociodemographic characteristics of the study participants

A total of 1982 weighted study participants were included to explore the predictors of late initiation of breast feeding. Among them, 1487 (75.03%) resided in rural areas. Regarding the maternal educational level, 956 (48.23%) had no formal education. Additionally, 950 (47.93%) mothers were at the poor wealth index level (table 2).

Table 2.

Sociodemographic characteristics of the study participants in Ethiopia, EDHS 2019

Variables	Categories	Weighted frequency (%)	Breastfeeding initiation time
			Early	Late
Sex of the child	Male	985 (49.7%)	724 (36.5%)	261 (13.2%)
	Female	997 (50.3%)	735 (37.1%)	262 (13.2%)
Age of the mother	15–24	637 (32.1%)	452 (22.8%)	193 (9.7%)
	25–34	1036 (52.3%)	760 (38.4%)	272 (13.7%)
	35–49	309 (15.6%)	242 (12.5%)	58 (2.9%)
Religion	Orthodox	605 (30.5%)	428 (21.6%)	177 (8.9%)
	Protestant	372 (18.8%)	281 (14.2%)	91 (4.6%)
	Muslim	969 (48.9%)	723 (36.5%)	246 (12.4%)
	Other	36 (1.8%)	27 (1.4%)	9 (0.4%)
Place of residence	Urban	495 (24.9%)	372 (18.8%)	123 (6.2%)
	Rural	1487 (75.0%)	1087 (54.8%)	400 (20.2%)
Educational status	No education	956 (48.2%)	705 (35.6%)	252 (12.7%)
	Primary education	697 (35.2%)	510 (25.7%)	187 (9.4%)
	Secondary education	197 (9.9%)	143 (7.2%)	53 (2.7%)
	Higher education	132 (6.7%)	101 (5.1%)	31 (1.6%)
Marital status	Married	1866 (94.2%)	1370 (69.1%)	496 (25.0%)
	Not married	116 (5.9%)	89 (4.5%)	27 (1.4%)
Wealth index level	Poor	950 (47.9%)	682 (34.4%)	268 (13.5%)
	Middle	280 (14.1%)	209 (10.5%)	71 (3.6%)
	Rich	752 (37.9%)	568 (28.7%)	184 (9.3%)
Media access (television)	Yes	393 (19.8%)	294 (14.8%)	99 (4.9%)
	No	1589 (80.2%)	1165 (58.8%)	424 (21.4%)
Media access (radio)	Yes	506 (25.5%)	379 (19.1%)	127 (6.4%)
	No	1476 (74.5%)	1080 (54.5%)	396 (19.9%)

(n=1982).

Maternal and reproductive characteristics

Nearly 25% of the participants had no ANC visit, and 42.8% of the mothers gave birth at home. Additionally, 7.1% of the mothers delivered their babies through caesarean section (table 3). The prevalence of late initiation of breastfeeding practice is 26.4% (95 CI 24.4 to 28.3).

Table 3.

Maternal and reproductive characteristics of mothers in Ethiopia, EDHS 2019

Variables	Categories	Weighted frequency (%)	Breastfeeding initiation time
			Early	Late
ANC visit	No ANC visit	505 (25.5%)	339 (17.1%)	166 (8.4%)
	1–3 visit	649 (32.8%)	484 (24.4%)	165 (8.3%)
	4 and above visit	828 (41.8%)	636 (32.1%)	192 (9.7%)
Place of delivery	Home	849 (42.8%)	591 (29.8%)	258 (13.0%)
	Health institution	1133 (57.2%)	868 (43.8%)	265 (13.4%)
Mode of delivery	SVD	1842 (92.9%)	1389 (70.1%)	453 (22.9%)
	Caesarean section	140 (7.1%)	70 (3.5%)	70 (3.5%)
Twin or single birth	Single birth	1964 (99.1%)	1446 (72.9%)	518 (26.1%)
	Twin	18 (0.9%)	13 (0.6%)	5 (0.3%)
Parity	1–2	851 (42.9%)	600 (30.3%)	251 (12.7%)
	3–4	541 (27.3%)	407 (20.5%)	134 (6.8%)
	5 and above	590 (29.8%)	452 (22.8%)	138 (6.9%)
Birth order	1–3	1159 (58.5%)	830 (41.9%)	329 (16.7%)
	4–6	564 (28.5%)	429 (21.6%)	135 (6.8%)
	6 and above	259 (13.1%)	200 (10.1%)	59 (2.9%)

(n=1982).

ANC, antenatal care; SVD, spontaneous vaginal delivery.

Multicollinearity test

VIF and tolerance values were used to check the existence of multicollinearity between variables. A VIF above 4 or a tolerance below 0.25 indicated that multicollinearity might exist. In this study, the maximum VIF was 2.04 with a mean VIF of 1.55, and the minimum tolerance value was 0.49. Thus, there is no multicollinearity between covariates (online supplemental file 1).

Multilevel analysis

Model comparison and random effects

The ICC in the null model showed that 17.5% of the difference in the late initiation of breast feeding resulted from cluster (enumeration area) differences. Furthermore, the MOR value in the null model revealed that 2.22 times the odds of differences in late initiation of breast feeding between the study subjects were attributed to differences in clusters. The PCV in the final model explained that 13.5% of the variation in the late initiation of breast feeding was due to individual and community-related factors. DIC (Deviance information criterion) and log-likelihood were computed for model comparison. A model with a small DIC and a high log-likelihood was declared the best-fitted model. Thus, model 4 was the best-fitted model (DIC=2213.34, log-likelihood=−1095.01) (online supplemental file 2).

Predictors of late initiation of breast feeding

The results of multivariable multilevel mixed-effect logistic regression analysis (model 4) revealed that the age of the mother, ANC visit, place of delivery and mode of delivery were the predictors of late initiation of breast feeding. The odds of late initiation of breast feeding among mothers in the 15–24 and 25–34 age groups were 1.66 (AOR=1.66, 95% CI 1.06 to 2.62) and 1.57 (AOR=1.57, 95% CI 1.09 to 2.25) times greater, respectively than those among mothers in the 35–49 age group. Mothers who had no ANC visits were 45% more likely to delay breastfeeding initiation than were those in the reference group (AOR=1.45, 95% CI 1.04 to 2.02). Home delivery increased the odds of late initiation of breast feeding by 53% compared with giving birth in a health institution (AOR=1.53, 95% CI 1.14 to 2.06). Mothers who gave birth through caesarean section were 4.79 times (AOR=4.79, 95% CI 3.19 to 7.21) more likely to delay the initiation of breast feeding than those who gave birth through spontaneous vaginal delivery (table 4).

Table 4.

Multivariable multilevel logistic regression analysis of determinants of late initiation of breast feeding in Ethiopia, EDHS 2019

Variables	Model 2 AOR (95% CI)	Model 3 AOR (95% CI)	Model 4 AOR (95% CI)
Age of the mother
15–24	1.74 (1.11 to 2.74)**		1.66 (1.06 to 2.62)**
25–34	1.59 (1.12 to 2.28)**		1.57 (1.09 to 2.25)**
35–49	1		1
Educational status
No education	1		1
Primary education	1.02 (0.76 to 1.35)		1.02 (0.77 to 1.37)
Secondary education	0.95 (0.62 to 1.46)		0.96 (0.64 to 1.48)
Higher education	0.73 (0.44 to 1.22)		0.75 (0.44 to 1.26)
Marital status
Married	1		1
Not married	0.76 (0.45 to 1.25)		0.75 (0.45 to 1.25)
Wealth index level
Poor	1		1
Middle	0.98 (0.68 to 1.43)		1.08 (0.74 to 1.58)
Rich	0.97 (0.69 to 135)		1.10 (0.78 to 1.54)
Media access (television)
No	1		1
Yes	0.99 (0.66 to 1.49)		1.11 (0.71 to 1.75)
Media access (radio)
No	1		1
Yes	0.96 (0.75 to 1.22)		0.97 (0.76 to 1.24)
ANC visit
No ANC visit	1.49 (1.08 to 2.08)**		1.45 (1.04 to 2.02)*
1–3 visit	1.11 (0.87 to 1.42)		1.09 (0.85 to 1.39)
4 and above visit	1		1
Place of delivery
Health institution	1		1
Home	1.56 (1.15 to 2.09)**		1.53 (1.14 to 2.06)***
Mode of delivery
SVD	1		1
Caesarean section	4.58 (3.04 to 6.89)***		4.79 (3.19 to 7.21)***
Child is Twin
No	1		1
Yes	1.10 (0.37 to 3.23)		1.08 (0.37 to 3.18)
Parity
1–2	1		1
3–4	0.82 (0.59 to 1.12)		0.81 (0.59 to 1.11)
5 and above	0.81 (0.49 to 1.33)		0.79 (0.47 to 1.30)
Birth order
1–3	1		1
4–6	0.91 (0.59 to 1.37)		0.90 (0.59 to 1.37)
6 and above	0.97 (0.53 to 1.78)		0.97 (0.52 to 1.79)
Place of residence
Urban		1	1
Rural		1.07 (0.79 to 1.45)	1.10 (0.71 to 1.73)
Community poverty level
Lower		1	1
Higher		1.18 (0.98 to 1.56)	1.17 (0.84 to 1.62)
Region
Metropolitan		1	1
Small peripheral		1.13 (082 to 1.56)	1.08 (0.78 to 1.49)
Large central		0.97 (0.69 to 1.34)	0.84 (0.60 to 1.16)

*, **, *** means significant at p < 0.05, p < 0.01 and p < 0.001 respectively.

AOR, adjusted odds ratio; SVD, spontaneous vaginal delivery.

Discussion

This study employed multilevel modelling to identify the predictors of late initiation of breastfeeding practice. Four models were considered. The first (null) model assumes only the dependent variable to explore the degree of cluster variation in late initiation of breast feeding. The second model and the third model include individual-level factors and community-level factors, respectively. The fourth model was adjusted for both the individual and community levels concurrently. Thus, DIC and log-likelihood were computed for model selection. Based on a low DIC and a high log-likelihood value, model 4 was found to be the best model to assess the predictors of late initiation of breastfeeding practice. We found that 26.4% of the children did not start breast feeding within the recommended time. According to model 4, young mothers, mothers without ANC visits, home births and births through caesarean section were found to be the predictors of late initiation of breastfeeding practice in Ethiopia.

The results of this study revealed that the prevalence of late initiation of breast feeding was higher than that reported in studies conducted in Ethiopia (Motta town) (21.2%),⁵⁰ Ghana (18%)⁵¹ and Sri Lanka (16.5%).⁵² In contrast, this finding is lower than the rates found in previous studies in Ethiopia, specifically in Arba Minch Zuria (57.2%)⁵³ and Debre Berhan town (37.4%).³¹ Additionally, the prevalence observed in this study is lower than the rates reported in the United Arab Emirates (37%),⁵⁴ Tanzania (49%),³⁵ Brazil (52.9%),⁵⁵ Nigeria (65.3%)⁵⁶ and Bangladesh (61.5%). This discrepancy might be attributed to variations in the use of healthcare services, community wealth level, culture, taboos towards the first breast milk (colostrum), religion and methodology between studies.

A systematic review published in 2017 reported that 38.6% of children in Ethiopia did not initiate breast feeding within the recommended time.⁵⁷ This significant discrepancy highlights the importance of considering geographic variations when interpreting national infant feeding data. The studies included in the review focused on specific regions only. In contrast, our study strengthens the understanding of breastfeeding initiation practices in Ethiopia by using a nationally representative dataset. This ensures that our results encompass diverse geographical and socioeconomic realities across the country. While the percentage of early initiation of breast feeding in Ethiopia witnessed significant fluctuations between 2000 and 2016, the overall trend paints a promising picture. Starting at 51% in 2000, it climbed to a peak of 69% in 2005, demonstrating notable success in promoting early breastfeeding practices. Although there was a subsequent decrease to 52% in 2011, the rebound to 73% by 2016³² suggests sustained efforts and potentially a shift towards more positive attitudes towards early breast feeding. This indicates an improvement in promoting breastfeeding practices and potentially better child health outcomes.

This study revealed that maternal age is a determinant of late initiation of breastfeeding practice. Young mothers were more than one and a half times more likely to have late initiation of breast feeding than older mothers were. As the mother’s age increases, the initiation of breastfeeding practice occurs earlier. This result is consistent with a study conducted in the United Arab Emirates.⁵⁸ A possible explanation might be that as the mother’s age increases, the likelihood of experiencing adverse outcomes from late initiation of breast feeding in the previous child rises. Additionally, youth are more susceptible to unwanted pregnancies,⁵⁹ and the newborn baby might not receive all the necessary attention immediately after birth. Furthermore, young mothers might lack experience in using maternal health services, leading to poor knowledge regarding the importance of early initiation of breastfeeding practices. Thus, incorporating health education sessions for youth and providing friendly services regarding the benefits of timely initiation of breast feeding is crucial.

Ensuring that young mothers receive clear and accessible information regarding the crucial benefits of early breastfeeding initiation, colostrum feeding and proper techniques are paramount. This support can be provided through individualised counselling, interactive group workshops or culturally appropriate educational materials tailored to their preferred learning styles. Recognising that young mothers may face unique challenges such as fear of pain, lack of confidence or logistical hurdles; open communication is the key to identifying specific concerns and providing personalised support. Establishing peer support groups and connecting them with experienced breastfeeding mentors can offer practical advice, encouragement and a sense of community, thereby boosting mothers’ confidence and fostering successful breastfeeding journeys. Furthermore, current research suggests that early skin-to-skin contact facilitates immediate neonatal breastfeeding initiation, enhances exclusive breastfeeding rates for 1 to 4 months post partum and prolongs overall breastfeeding duration.⁶⁰ Additionally, infants who experience skin-to-skin contact exhibit increased maternal engagement and less crying behaviour.

Late initiation of breastfeeding practice is significantly higher among mothers with no ANC visit than among those who have received ANC. This finding is supported by studies conducted in Uganda⁶¹ and Namibia.³² Mothers who attended ANC visits may have been informed about the importance of timely initiation of breast feeding for child health, leading them to start breast feeding at an earlier convenience. Moreover, the more ANC visits women attend, the greater their contact with healthcare professionals, facilitating health information exchange. Consequently, mothers may be more likely to initiate breast feeding within the first hour. Enhancing ANC availability through mobile clinics, convenient appointment times and transportation assistance is recommended. Additionally, sharing success stories and positive testimonies from mothers who have benefited from ANC breastfeeding support can significantly contribute to promoting the early initiation of breastfeeding practice.

Mothers who gave birth at home are more likely to initiate breast feeding later than mothers who delivered at health institutions. This finding is consistent with studies conducted in Malawi,⁶² Northern Uganda⁶³ and low-income and middle-income countries.⁸ The possible reason for this disparity in late initiation of breast feeding could be that mothers who gave birth at home might not be exposed to health education and additional guidance from healthcare professionals regarding the health benefits of initiating breast feeding earlier. In Ethiopia, the prevalence of home deliveries reaches 66.7%.⁶⁴ Moreover, home deliveries in Ethiopia lack support from skilled birth attendants. Reducing home deliveries might significantly prevent adverse health outcomes in newborns who experience late initiation of breast feeding. Improving access to and the quality of maternal healthcare services in rural areas and for marginalised communities is essential for reducing home deliveries and achieving timely initiation of breastfeeding practices. This includes ensuring the availability of skilled birth attendants and emergency medical services in areas with prevalent home births. Educating communities about the potential risks and complications of home births, especially when high-risk factors are present, can also play a significant role. Additionally, reducing financial and logistical barriers to accessing healthcare facilities, such as transportation costs or a lack of childcare options, is crucial. Finally, addressing cultural beliefs or misconceptions about facility births through community outreach and engagement is key to promoting facility births and fostering timely breastfeeding initiation.

Late initiation of breastfeeding practice is significantly higher among children born through caesarean section. Studies conducted in Bangladesh,²⁸ the United Arab Emirates⁶⁵ and South Sudan²⁰ have reported similar findings. Women who give birth via caesarean section might not be conscious enough immediately after delivery to initiate breast feeding due to the effects of anaesthesia. The WHO implementation guidelines for early initiation of breast feeding after caesarean section births assert that when a woman has difficulty initiating breast feeding due to any medical procedure, the child must be put on the breast immediately when she is conscious.⁶⁶ Therefore, any effort to reduce the caesarean section rate significantly improves breastfeeding initiation practices. Whenever medically possible, advocate for placing the baby directly on the mother’s chest after a caesarean section. This promotes skin-to-skin contact and early breastfeeding attempts, which are crucial for establishing successful breastfeeding practices. Additionally, breastfeeding rates among caesarean section mothers should be closely tracked and interventions should be consistently adopted based on data and feedback.

This study uses data encompassing the entire country, rendering its findings relevant and generalisable to Ethiopian children as a whole. The large sample size inherent in nationally representative data provides the study with greater statistical power. Despite the advantages of national scope, relying on existing secondary data restricts the exploration of additional factors beyond those already collected. This limitation may impede the identification of further potential predictors of late breastfeeding initiation. The cross-sectional nature of the data poses a challenge in establishing causal relationships between the explanatory and outcome variables.

Conclusion

Despite the WHO recommendations to initiate breast feeding within 1 hour after birth, more than one-fourth of newborns start breast feeding late. Maternal age, ANC visit frequency, mode of delivery and place of delivery were identified as significant predictors of late initiation of breastfeeding practices.

To address the observed delay among specific groups, a multi-pronged approach is crucial. The development of targeted prenatal education programmes focused on emphasising the importance of early initiation is essential for young mothers. This approach should address their specific concerns and anxieties. Additionally, providing additional peer support groups or individual mentoring during pregnancy and post partum can promote early initiation. For mothers with infrequent ANC visits, integrating early initiation education into every encounter, regardless of schedule, is the key. Outreach programmes and mobile clinics can bridge the gap for those missing appointments, while accessible educational materials in local languages can further spread awareness. Healthcare providers, particularly in hospitals, need training to prioritise immediate skin-to-skin contact, even during caesarean sections. Having readily available lactation consultants providing essential support is crucial. For mothers choosing home births, collaboration with midwives and community health workers is vital. Educating them on early initiation and its benefits, along with equipping them to guide mothers through the process, is crucial. Establishing postpartum home visit programmes for these mothers, staffed by lactation consultants or trained community workers, can offer the critical support needed for successful exclusive breast feeding. By implementing these targeted interventions, we can bridge the gap and ensure that all mothers, regardless of their background or birth experience, have the knowledge and support they need to initiate breast feeding early and reap its lifelong benefits for themselves and their babies.

Future research outlook

Qualitative research: conduct in-depth interviews or focus groups with mothers who delayed initiation to gain insights into their specific reasons, concerns and experiences. This approach can help tailor interventions to address their unique needs and challenges. Behavioural and cultural factors: to explore the influence of cultural beliefs and practices on breastfeeding initiation in diverse communities. Understanding these factors can guide the development of culturally sensitive interventions and community engagement strategies. Healthcare system factors: investigate potential barriers within healthcare systems that may contribute to delayed initiation, such as a lack of lactation support, inadequate staffing or policies that hinder skin-to-skin contact. Identifying these factors is crucial for implementing effective changes and improving breastfeeding initiation practices.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

Ethical approval was not needed because the study used publicly available data. However, permission to use the data for the study was obtained from the Demographic Health Survey programme. Informed consent was obtained at the beginning of each interview by the EDHS data collectors.