Geographic inequalities in exclusive breastfeeding among infants under six months across 18 African countries

Abstract

Background

Exclusive breastfeeding (EBF) is essential for infant survival, growth, and development. Despite known benefits, national averages often mask adherence to coverages and underlying geographic inequalities. While previous studies have examined national averages, less is known about how EBF rates vary within countries. This study assessed national and subnational disparities in EBF among infants under six months across 18 African countries using comparable 2019 estimates.

Methods

This retrospective cross-sectional ecological analysis used existing 2019 modelled EBF estimates from the Institute for Health Metrics and Evaluation (IHME), accessed through the World Health Organization (WHO) Health Equity Assessment Toolkit (HEAT, 2024 update). EBF estimates follow the WHO 24-hour recall definition for infants aged 0–6 months. Geographic inequalities were quantified using difference (D), ratio (R), population attributable risk (PAR), and population attributable fraction (PAF) using WHO HEAT’s built-in analytical tools. Spatial patterns were visualised using QGIS.

Results

National prevalence of EBF ranged from 14.4% in Comoros to 65.9% in São Tomé and Príncipe. Only Ghana, Lesotho, São Tomé and Príncipe, and Zambia exceeded the 2019 global average of 43.5%. Subnational disparities were evident across nearly all countries, with the widest inequalities observed in Nigeria (D = 38.24, R = 9.13, PAF = 116.55%), Tanzania (D = 46.8, R = 2.69, PAF = 42.5%), and Cameroon (D = 24.21, R = 2.67, PAF = 45.48%). In contrast, São Tomé and Príncipe, Lesotho, Comoros, and Eswatini showed minimal regional variation (D ≤ 6, PAF < 7%). On average, one-third of national disparities could be reduced if all regions matched the prevalence of the best-performing areas.

Conclusion

EBF coverage across the 18 African countries remains highly uneven despite sustained global and national promotion efforts. While a small number of countries have achieved relatively high and uniform coverage, most continue to experience pronounced subnational gaps. Addressing these inequalities will require region-specific breastfeeding interventions, strengthened maternal support systems, and the systematic integration of equity considerations into national nutrition programmes. Enhanced subnational monitoring and multi-sectoral action will be essential for accelerating equitable progress toward the WHO global nutrition target of 70% EBF by 2030.

Background

Breastfeeding provides optimal nourishment for infant survival, growth, and development [1]. Beyond its benefits for the child, breastfeeding contributes to maternal well-being, supports postpartum recovery, and reduces the risk of several diseases in both infants and mothers [1, 2]. In addition to biological benefits, breastfeeding also contributes to social equity and poverty reduction [3]. This assertion is reinforced by James P. Grant, former UNICEF Executive Director, who noted that “Breastfeeding is a natural safety net against the worst effects of poverty. If a child survives the first month of life, exclusive breastfeeding goes a long way towards cancelling out the health difference between being born into poverty and being born into affluence.” From an economic perspective, breastfeeding is the least expensive and safest method of infant feeding [2]. Socially, it is regarded as a basic human right [3]. The evidence indicates that inadequate breastfeeding practices contribute substantially to preventable child deaths and disabilities [4]. As such, approximately 1.4 million children are estimated to die each year, and approximately 44 million suffer disabilities as a result of suboptimal breastfeeding [5]. The health advantages for both mothers and children depend on the frequency, duration, and exclusivity of breastfeeding [6]. Exclusive breastfeeding (EBF) is widely recognised as a cornerstone of infant nutrition and health promotion [1]. The World Health Organization (WHO) recommends EBF during this period because EBF provides essential nutrients for growth and development, protects against diseases, and reduces the risk of infant mortality [3].

The WHO and UNICEF have implemented several initiatives to promote, protect, and strengthen the advocated gains of EBF. Notably, the Baby-Friendly Hospital Initiative and the International Code of Marketing of Breast Milk Substitutes were launched [7]. These programs aimed to improve breastfeeding practices globally and address the persistent decline in EBF rates [7]. In 2018, the WHO and UNICEF, together with other partners, emphasised the need for family-friendly workplaces and social policies to support mothers in nurturing and bonding with their children [8]. In addition, the WHO designated the first week of August as World Breastfeeding Week to raise awareness and encourage collective global action [3]. Despite these extensive efforts, global adherence to EBF remains suboptimal [9]. Within Africa, for example, the pattern of progress is particularly uneven. While some countries have recorded improvements, national averages often mask substantial geographic disparities in EBF practices. For example, the Ghana Demographic and Health Survey (2022) reported that although the prevalence of breastfeeding was high (96.8%), the duration and exclusivity of breastfeeding were low, with only approximately 52% of children aged 0–5 months being exclusively breastfed [10]. This persistent gap makes inadequate adherence to EBF a significant and continuing public health concern in both developed and developing regions [6]. These disparities may be attributable to variations in access to maternal health services, sociocultural norms, levels of economic development, and the implementation of breastfeeding promotion policies [6, 11]. Therefore, understanding these spatial inequalities is essential for designing interventions that ensure equitable progress toward the WHO global nutrition target of 70% EBF by 2030 [12].

Although earlier studies have explored national trends and determinants of EBF, there is limited empirical evidence comparing subnational inequalities across multiple African countries using harmonised data. This knowledge gap is likely to constrain policymakers and public health stakeholders from addressing region-specific barriers and allocating resources effectively. Moreover, while country-specific data on EBF have been available for several decades, the most current harmonised subnational data suitable for cross-country comparisons are available only for the year 2019 in the WHO Health Equity Assessment Toolkit (HEAT). Therefore, this study examined the extent of geographic inequalities in EBF among infants under six months of age across 18 African countries via comparable 2019 data from the WHO HEAT. In global monitoring systems, including the WHO HEAT database used in this study, EBF is measured using a 24-hour recall of feeding practices among infants aged 0–6 months. Conceptually, this study contributes to the growing field of health equity and spatial epidemiology by illustrating how within-country inequalities are likely to persist even amid national improvements in maternal and child health indicators. This finding reinforces the importance of analysing breastfeeding data through an equity lens, which is consistent with the WHO Commission on Social Determinants of Health framework, which identifies “place” as a fundamental determinant of health outcomes. Practically, the findings provide evidence to guide regionally tailored breastfeeding promotion strategies within African countries. Identifying areas where inequalities are most pronounced or improving could help governments, NGOs, and international agencies intervene more effectively, thereby accelerating progress toward the global nutrition target of 70% EBF coverage by 2030 [12].

Methods

Study design and data source

This study employed a retrospective cross-sectional ecological design, using existing 2019 secondary data on exclusive breastfeeding (EBF) among infants under six months of age. The data were drawn from the Institute for Health Metrics and Evaluation (IHME), accessed through the World Health Organization (WHO) Health Equity Assessment Toolkit (HEAT), 2024 update, which hosts retrospectively modelled registry-based estimates for the year 2019 [13]. The HEAT toolkit provides a structured platform for assessing health inequalities by integrating disaggregated health indicator data from the WHO Health Inequality Data Repository [13]. Moreover, the HEAT database provides harmonised, modelled estimates of key health indicators across countries and subnational regions, allowing for comparative analyses of health outcomes and inequalities over time [14]. Although there are earlier harmonised and comparable subnational disaggregation data across 18 countries, the 2019 dataset was the most recent.

Study setting and country selection

Eighteen African countries were included on the basis of the availability of subnational disaggregated EBF data in the HEAT 2024 dataset. These included West Africa (Benin, Côte d’Ivoire, Ghana, Guinea, Mauritania, Nigeria, Senegal), Central Africa (Cameroon, Democratic Republic of the Congo, São Tomé and Príncipe), East Africa (Comoros, Kenya, United Republic of Tanzania, Zambia), and Southern Africa (Eswatini, Lesotho, Zimbabwe, Angola) (Fig. 1). This grouping was based on the United Nations geoscheme for Africa. Country selection was based entirely on the availability of comparable 2019 subnational EBF estimates in the WHO HEAT database. As a result, northern and northeastern African countries are not represented in the dataset.

Fig. 1.

Map of Africa showing selected study areas. The map was self-designed with QGIS. Basemap shapefiles are accessible. https://www.geoboundaries.org/countryDownloads.html

Measure

The outcome variable was the prevalence of EBF among infants aged 0 to 6 months. In accordance with WHO definitions, exclusive breastfeeding refers to feeding infants only breast milk (including expressed milk) and no other liquids or solids, except for oral rehydration solution, drops, or syrups of vitamins, minerals, or medicines, during the first six months of life [1]. It is worth noting that EBF estimates in the HEAT database are based on the WHO 24-hour recall definition for infants aged 0–6 months. This is a current-status indicator rather than a cumulative measure of feeding from birth. The equity stratifier used in this study was the geographic distribution of EBF within each country.

Measurement of geographic inequalities

To quantify within-country disparities in EBF, both absolute and relative measures of inequality were analysed via the HEAT 2024 toolkit. The selected summary measures were difference (D), ratio (R), population attributable risk (PAR), and population attributable fraction (PAF). These summary measures were selected in line with the World Health Organization’s recommended framework for health inequality monitoring, which advocates the combined use of absolute and relative measures to capture both the magnitude and proportional distribution of inequalities across population subgroups [13, 15]. D measures the absolute difference between the regions with the highest and lowest EBF prevalence within each country [16]. Similarly, R represents the relative difference, which is computed as the ratio of EBF prevalence in the highest-performing region to that in the lowest-performing region [16]. Moreover, PAR estimates the difference between the national average and the rate in the best-performing region, indicating potential improvement if all regions achieve the highest observed prevalence [16]. Finally, the PAF estimates the proportional equivalent of PAR, expressed as a percentage [16]. Together, these measures provide a comprehensive view of both the magnitude and proportional extent of geographic inequalities.

Difference (D) is expressed as:

where and represent the prevalence of EBF in the highest-performing and the lowest-performing regions, respectively. A positive D indicates higher prevalence in the highest-performing region, while a negative value indicates higher prevalence in the lowest-performing region.

Secondly, Ratio (R) is expressed as:

A ratio greater than 1 indicates that EBF is relatively more common in the highest-performing region, while a ratio below 1 indicates that the lowest-performing region has a higher prevalence.

Likewise, Population Attributable Risk (PAR) was computed as:

where is the overall national prevalence and denotes the prevalence in the reference group (highest-performing region).

Finally, the Population Attributable Fraction (PAF) is expressed as:

Higher PAF values indicate a greater potential for improving national EBF levels if regional inequalities were eliminated.

Data analysis and presentation

All analyses were conducted with the statistical tools embedded in the WHO HEAT online software (2024 update). The platform automatically computes summary inequality measures with corresponding 95% intervals. The extracted results were exported to Microsoft Excel for data management, tabulation, and graphical presentation. The findings are summarised in both tables and charts, highlighting the national prevalence of EBF and subnational (regional) variations in inequality indicators for the year 2019. Spatial visualisation was conducted with QGIS version 3.44.3. The resulting choropleth maps displayed the magnitude and spatial distribution of EBF prevalence with a graduated colour scale. The spatial patterns were interpreted in conjunction with descriptive statistics and regional averages to contextualise disparities.

Results

Prevalence of exclusive breastfeeding (EBF) among infants under six months

The national prevalence and spatial distribution of EBF among infants under six months of age for 18 African countries based on 2019 data from the World Health Organization (WHO) Health Equity Assessment Toolkit (WHO HEAT 2024) dataset are presented in Table 1; Fig. 2. Table 1 presents the national prevalence of EBF, while Fig. 2 situates these estimates within a geographic context. Across all 18 selected countries, EBF prevalence ranged from 14.39% in Comoros to 65.93% in São Tomé and Príncipe. Among the included 18 countries, those located in the southern and eastern part of the continent (such as Zambia [58.69%], Lesotho [57.89%], and Tanzania [52.26%]) generally recorded higher EBF rates than countries in western and central Africa (including Côte d’Ivoire [17.57%], Nigeria [19.83%], and Cameroon [26.62%]). Compared with the global average of 43.5% in 2019, only four countries (Ghana [49.7%], Lesotho [57.9%], São Tomé and Príncipe [65.9%], and Zambia [58.7%]) exceeded the global threshold (Fig. 2). In contrast, the majority of countries included in this study reported EBF rates below the global average, with the lowest recorded rates in Comoros (14.4%), Côte d’Ivoire (17.6%), and Nigeria (19.8%).

Table 1.

National prevalence of exclusive breastfeeding (EBF) among infants under six months (2019)

Countries	National prevalence [%]	UN geoscheme region	Comparison with global average [≥43.5%]
Angola	39.54	Southern Africa	Below Global Average
Benin	41.18	West Africa	Below Global Average
Cameroon	26.62	Central Africa	Below Global Average
Comoros	14.39	East Africa	Below Global Average
Côte d’Ivoire	17.57	West Africa	Below Global Average
Democratic Republic of the Congo	24.49	Central Africa	Below Global Average
Eswatini	42.48	Southern Africa	Below Global Average
Ghana	49.67	West Africa	Above Global Average
Guinea	22.31	West Africa	Below Global Average
Kenya	33.43	East Africa	Below Global Average
Lesotho	57.89	Southern Africa	Above Global Average
Mauritania	39.69	West Africa	Below Global Average
Nigeria	19.83	West Africa	Below Global Average
São Tomé and Príncipe	65.93	Central Africa	Above Global Average
Senegal	38.40	West Africa	Below Global Average
United Republic of Tanzania	52.26	East Africa	Below Global Average
Zambia	58.69	East Africa	Above Global Average
Zimbabwe	40.07	Southern Africa	Below Global Average

%: Percentage; ≥: Greater than or equal to

Source: WHO Health Inequality Data Repository (HEAT 2024 update), based on IHME estimates for 2019

Fig. 2.

Spatial distribution of prevalence of exclusive breastfeeding (EBF) across 18 African countries in 2019

Magnitude and pattern of geographical inequalities in exclusive breastfeeding (EBF) among infants under six months across 18 countries

In addition to national averages, notable regional disparities in EBF prevalence were detected within countries (Fig. 3). In Angola, the prevalence ranged from 27.1% in Lunda Norte to 55.1% in Namibe, yielding a difference (D) of 28.0 (Table 1). Provinces such as Namibe, Huíla, and Zaire recorded EBF rates well above the national average. As shown in Table 1, the population attributable fraction (PAF) was 39.3%, indicating that national EBF could increase by nearly 40% if all provinces achieved the prevalence observed in the Namibe region. The population attributable risk (PAR) of 15.5% indicates a moderate absolute gain potential, whereas the ratio (R = 2.03) shows that infants in the Namibe region were twice as likely to be exclusively breastfed than those in the Lunda Norte region. Similarly, in Benin, EBF prevalence ranged from 29.2% in the Littoral region to 51.5% in the Couffo region, producing a D of 22.3 (Table 1) around the national average of 41.2%. Regions such as Alibori, Atacora, Collines, and Couffo recorded EBF rates well above the national average, whereas Atlantique, Donga, Littoral, Mono, and Ouémé had considerably lower coverage rates (Fig. 3). The PAF (25.2%) implies that a quarter of the current national disparity could be bridged if all regions matched the rate in Couffo. In addition, the PAR (10.4%) indicates the absolute percentage increase that could occur nationally if every region reached the prevalence in Couffo. The R value of 1.76 indicated that the prevalence in Couffo was nearly 1.8 times greater than the prevalence in the Littoral region (Table 1).

Fig. 3.

Regional distribution of exclusive breastfeeding prevalence among infants under six months of age in 18 countries in 2019

In Cameroon, the regional EBF prevalence ranged from 14.5% in Far North province to 38.7% in Northwest province, yielding a D of 24.2 (Table 1) around the national average of 26.6%. Provinces such as Central, East, Littora, Northwest, South, Southwest, and West regions recorded EBF rates well above the national average (Fig. 3). The PAF (45.5%) was among the highest observed, indicating that national EBF could improve by nearly half under full regional equity. The PAR (12.1%) suggested considerable absolute gain. Moreover, the R value of 2.67 highlighted that the EBF prevalence in the Northwest Region was more than two times greater than that in the Far North Region (Table 1(. Moreover, EBF coverage varied moderately across provinces in Comoros. The prevalence ranged from 11.6% in Mwali to 14.9% in Ndzuwani, with a D of approximately 3.4 around the national average of 14.4%. The recorded rates of Ndzuwani were above the national average, whereas those of Mwali and Ngazidja were below (Fig. 3). The PAF was modest at 3.9%, whereas the PAR stood at 0.6%, implying very small potential national gains from equalising regional performance. The R value of 1.29 indicated minimal disparity between the Ndzuwani and Mwali regions. Overall, Comoros presented the least spatial inequality in EBF among the assessed countries (Table 1(.

Furthermore, in Côte d’Ivoire, EBF prevalence ranged from 14.6% in Ouémé to 24.1% in Zanzan, with a D of 9.5 (Table 1) around the national average of 17.6%. Only Lacs, Montagnes, Vallée du Bandama, and Zanzan recorded prevalences above the national average (Fig. 3). A PAF of 37% implies that more than one-third of the national gap could close if all regions reached the prevalence observed in Zanzan. The PAR (6.5%) indicates possible absolute improvement in national coverage. The R of 1.65 shows that the rate was roughly two times that of the Ouémé region (Table 1(. In the Congo, variation was also notable. EBF prevalence ranged from 21.4% in Brazzaville to 28.3% in Pool, yielding a D of approximately 6.9 around the national average of 24.5%. As illustrated in Fig. 3, Bouenza, Likouala, Plateaux, and Pool recorded rates above the national average. The PAF was 15.2%, whereas the PAR was 3.7%, representing the share and absolute improvement achievable through equalisation. Thus, national disparity in EBF incidence could be removed if low-level provinces matched those in Bouenza, Likouala, Plateaux, and Pool. The R value (1.32) confirms that the differences are proportionally small (Table 1). In contrast, Eswatini showed relatively small interprovincial differences. The prevalence ranged from 40.2% in Shiselweni to 44.1% in Hhohho, depicting a narrow D of approximately 3.9 around the national average of 42.5%. Hhohho and Lubombo recorded rates above the national level, whereas Manzini and Shiselweni reported lower rates (Fig. 33). With a PAF below 4%, improving low-performing areas to match the prevalence in the Hhohho and Lubombo regions would produce only modest national gains. The PAR (1.6%) translates this to a minimal absolute improvement. The R value (1.10) confirms the limited relative inequality (Table 1).

EBF coverage varied more widely across regions in Ghana. The rates ranged from 42.1% in the Central Region to 68.6% in the Upper West Region, yielding a D of 26.5 around the national average of 49.7%. As shown in Fig. 3, Brong Ahafo, Northern, Upper East, and Upper West regions recorded rates above the national average. The PAF (38.1%) revealed that nearly two-fifths of national inequality could be attributed to geographic disparities. The PAR (18.9%) represented the possible national gain if all regions achieved rates in the Brong Ahafo, Northern, Upper East, and Upper West regions. In addition, R (1.63) demonstrated a substantial relative gap (Table 1(. In Guinea, the prevalence of EBF ranged from 19.3% in Boké to 28.1% in Conakry, representing a D of approximately 8.9 around the national average of 22.3%. As shown in Fig. 3, Conakry and Kindia recorded higher coverage above the national prevalence. The PAF (25.7%), PAR (5.7%) and R (1.45) all indicate moderate relative inequalities (Table 1(. A comparable pattern of variation was observed in Kenya, where EBF prevalence ranged from 26.9% in Mandera to 45.8% in Samburu. This yielded a D of 18.9, around the national average of 33.4%. Only Baringo, Elgeyo-Marakwet, Embu, Isiolo, Kajiado, Kiambu, Kirinyaga, Laikipia, Machakos, Marsabit, Meru, Murang’a, Nairobi, Nakuru, Nyandarua, Nyeri, Samburu, the Tana River, Tharaka-Nithi, Turkana, Vihiga, Wajir, and West Pokot recorded higher EBF levels above the national average (Fig. 3). The PAF (37.1%) suggested that more than one-third of national inequality could be attributed to regional variation. The PAR (12.4%) quantified the potential absolute improvement, whereas the R (1.70) reflected a substantial proportional difference (Table 1(.

Provincial disparities were also apparent in Lesotho. The coverage ranged from 55.9% in Qacha’s Nek to 61.8% in Mokhotlong. This corresponds to a D of 5.9, which points around the national average of 57.9%. Butha-Buthe, Mafeteng, Mokhotlong, and Thaba-Tseka recorded rates above the national level, whereas Berea, Leribe, Maseru, Qacha’s Nek, and Quthing were below (Fig. 3). The PAF was 6.8%, the PAR was 3.9%, and the R was 1.11, all of which suggest minimal inequality (Table 1(. Similarly, in Mauritania, EBF prevalence varied moderately across provinces, from 30.3% in Tiris Zemmour to 45.1% in Guidimaka. This signifies a D of approximately 14.8, around the national average of 39.7%. As illustrated in Fig. 3, Assaba, Brakna, Dakhlet Nouadhibou, Guidimaka, Hodh Ech Chargui, Hodh Ech Chargui, and Hodh el Gharbi presented higher prevalence rates above the national average. A PAF of 13.7% implies that just over one-tenth of the national disparity could be closed through regional equalisation, whereas the PAR (5.4%) quantifies the absolute gain. The R value (1.49) illustrates that infants in high-performing areas are approximately 50% more likely to be exclusively breastfed than those in lagging regions are (Table 1(.

Nigeria displayed the largest subnational inequality in exclusive breastfeeding among all 18 countries. The regional EBF prevalence ranged from 4.7% in Yobe to 42.9% in Osun. This denotes a D of 38.2 around the national average of 19.8%. Anambra, Bayelsa, Benue, Ebonyi, Edo, Ekiti, Federal Capital Territory, Kogi, Kwara, Lagos, Ondo, Osun, Oyo, Plateau, Rivers, Sokoto, and Taraba recorded higher levels of EBF above the national average (Fig. 3). The PAF (116.6%) indicates that the national prevalence could more than double if all regions reached the prevalence rate observed in Osun. The PAR (23.1%) and R (9.13) revealed that infants in the top regions were more than nine times as likely to be exclusively breastfed as those in the lowest regions were (Table 1). In São Tomé and Príncipe, the regional EBF prevalence ranged narrowly between 65.9% in São Tomé and 67.9% in Príncipe, yielding a D of just 2.1 around the national average of 65.9%. The PAF was 3.0%, the PAR was 2.0%, and the R value of 1.03 reflected near-equality between regions. This country displayed the most uniform subnational distribution of EBF in the entire dataset (Table 1(.

In Senegal, EBF prevalence ranged from 33.6% in Kaffrine to 51.9% in Kolda, producing a D of 18.3 around the national average of 38.4%. Only Dakar, Kolda, Louga, Saint-Louis, Sédhiou, Thiès, and Ziguinchor recorded higher coverage above the national mean prevalence (Fig. 3). The PAF (34.9%) indicated that one-third of national inequality was explained by spatial variation. The PAR (13.4%) quantified the potential absolute gain if parity was achieved, whereas the R value (1.54) reflected moderate proportional inequality (Table 1(. Substantial regional variation was also observed in the United Republic of Tanzania, where the prevalence ranged from 27.7% in Pemba South to 74.4% in Kigoma. This shows a D of nearly 46.8, around the national average of 52.3%. As presented in Fig. 3, only Dodoma, Geita, Iringa, Kagera, Katavi, Kigoma, Manyara, Mwanza, Shinyanga, Simiyu, Singida, and Tabora recorded coverages higher than the national average. The PAF (42.5%) indicated that more than two-fifths of the national EBF could be bridged if all regions matched the rate in Kigoma. The PAR (22.2%) and the R value (2.69) confirmed significant absolute and relative inequalities (Table 1(. Moreover, in Zambia, provincial EBF coverage ranged from 47.9% in Muchinga to 73.8% in Southern, producing a D of 25.9 around the national average of 58.7%. Central, Lusaka, Southern, and Western provinces recorded higher rates above the national mean (Fig. 3). The PAF (25.8%) suggests that one quarter of national inequality could be bridged if all regions match the rate in Southern province. The PAR (15.1%) quantifies the potential improvement, and the R (1.54) denotes moderate proportional disparity (Table 1(. Across the border, Zimbabwe displayed moderate provincial differences. The EBF prevalence ranged from 36.0% in Harbin to 50.6% in Matabeleland North, yielding a D of approximately 14.6 (Table 1) around the national average of 40.1%. EBF rates higher than the national prevalence were recorded in only Bulawayo, Masvingo, Matabeleland North, Matabeleland South, and Midlands (Fig. 3). A PAF of 26% shows that national improvement could be accelerated if all regions matched the rate in Matabeleland North. The PAR (10.6%) provides a clear quantitative target, whereas the R (1.41) indicates a 40% greater likelihood of EBF in the top regions (Table 1).

Table 2.

Geographical inequalities in exclusive breastfeeding (EBF) among infants under 6 months of age by country (2019)

Country	Prevalence (%) [95% CI]		Summary measures
	Highest Region (%)	Lowest Region (%)	D	PAF (%)	PAR (%)	R
Angola	55.07 [37.08, 73.20]	27.05 [15.33, 41.20]	28.01	39.28	15.53	2.03
Benin	51.54 [42.48, 59.31]	29.22 [20.75, 39.23]	22.32	25.15	10.36	1.76
Cameroon	38.72 [19.11, 61.98]	14.51 [5.33, 29.98]	24.21	45.48	12.11	2.67
Comoros	14.94 [3.67, 37.80]	11.58 [2.63, 29.34]	3.36	3.85	0.55	1.29
Cote d’Ivoire	24.09 [8.68, 47.68]	14.61 [4.06, 34.91]	9.47	37.11	6.52	1.65
Democratic Republic of the Congo	28.21 [10.51, 52.08]	21.35 [7.09, 42.51]	6.85	15.19	3.72	1.32
Eswatini	44.05 [24.41, 64.85]	40.18 [21.73, 60.94]	3.87	3.71	1.58	1.10
Ghana	68.60 [40.84, 89.72]	42.13 [15.66, 73.03]	26.47	38.14	18.94	1.63
Guinea	28.05 [8.32, 59.04]	19.32 [6.31, 42.25]	8.73	25.71	5.74	1.45
Kenya	45.81 [20.15, 71.25]	26.89 [10.14, 51.51]	18.92	37.06	12.39	1.70
Lesotho	61.80 [51.94, 71.29]	55.90 [46.35, 65.34]	5.90	6.76	3.91	1.11
Mauritania	45.12 [21.56, 70.86]	30.33 [10.61, 59.79]	14.79	13.69	5.43	1.49
Nigeria	42.94 [33.84, 51.80]	4.70 [3.20, 6.72]	38.24	116.55	23.12	9.13
São Tomé and Principe	67.91 [31.40, 93.04]	65.85 [30.13, 90.88]	2.06	3.01	1.99	1.03
Senegal	51.82 [30.09, 73.21]	33.56 [22.30, 45.82]	18.27	34.95	13.42	1.54
United Republic of Tanzania	74.44 [58.48, 86.22]	27.67 [10.02, 52.60]	46.76	42.45	22.18	2.69
Zambia	73.82 [51.69, 89.08]	47.88 [27.23, 68.54]	25.94	25.78	15.13	1.54
Zimbabwe	50.62 [33.73, 67.25]	35.98 [19.38, 57.56]	14.64	26.33	10.55	1.41

D: Difference; PAF: Population attributable fraction; PAR: Population attributable risk, R: Ratio; %: Percentage

Discussion

Exclusive breastfeeding (EBF) among infants under six months across the 18 countries

This study examined the national and regional distribution of exclusive breastfeeding (EBF) among infants under six months of age across 18 African countries using the World Health Organization (WHO) Health Equity Assessment Toolkit (HEAT) dataset. It revealed substantial variation in EBF coverage between and within countries. At the national level, the prevalence of EBF ranged from 14.4% in Comoros to 65.9% in São Tomé and Príncipe. Notably, Ghana, Lesotho, São Tomé and Príncipe, and Zambia were the only countries whose national prevalence surpassed the 2019 global average of 43.5% [17]. The majority of countries, particularly those in West and Central Africa, fell substantially below this benchmark. This uneven distribution highlights persistent challenges in achieving optimal EBF practices across much of the selected countries included in the study. The relatively higher prevalence of EBF observed in some of the selected southern and eastern African countries, such as Zambia (58.7%), Lesotho (57.9%), and Tanzania (52.3%), may indicate stronger policy implementation, broader community sensitisation, and more consistent enforcement of maternal and child health programmes [18, 19]. These regions have historically recorded higher antenatal care (ANC) attendance, greater integration of breastfeeding counselling into maternal health services, and better coverage of baby-friendly hospital initiatives [18–21]. In contrast, lower rates in countries such as Côte d’Ivoire (17.6%), Nigeria (19.8%), and Cameroon (26.6%) could stem from multiple intersecting factors, including weaker health system capacity, sociocultural norms that favour early introduction of complementary feeding, limited postnatal support, and urban lifestyle constraints [18, 21, 22]. Previous studies have also shown that maternal employment, inadequate maternity leave, and misconceptions about breast milk sufficiency remain key barriers to EBF in several West and Central African settings [18, 21–23].

It was also revealed that more than two-thirds of the countries included in the study remain below the global average. This highlights a significant implementation gap between international breastfeeding targets and national realities. While regional differences partly mirror socioeconomic and policy disparities, they also point to deeper structural inequalities in access to breastfeeding-friendly environments [11]. Health workforce shortages, inconsistent community-level follow-up, and limited enforcement of the International Code of Marketing of Breastmilk Substitutes continue to undermine progress in many of these low-performing countries [11, 24]. From a programmatic perspective, the variation observed between high- and low-performing countries suggests that national averages may obscure substantial intra-regional inequities [2, 6, 19]. This calls for renewed attention to subnational contexts, where progress could be accelerated by learning from local models of success. For example, countries such as Zambia and Lesotho demonstrate that higher EBF coverage is achievable when maternal health interventions are decentralised and sustained through community-based health promotion. Scaling up such context-specific approaches could help bridge the geographic inequalities identified in this study. These findings reaffirm that EBF practices across Africa are highly unequal both across and within countries. Therefore, addressing these disparities requires interventions that respond to local realities, sustained investment in maternal health systems, and stronger policy enforcement. Without such efforts, the continent risks stagnation in achieving global nutrition goals despite the well-documented benefits of EBF for child survival and development.

Magnitude and pattern of geographical inequalities in exclusive breastfeeding (EBF) among infants under six months across 18 countries

In addition to national averages, this study revealed considerable national and regional disparities in EBF coverage across the 18 countries. Nigeria presented the widest subnational gap, with the prevalence of EBF ranging from 4.7% in Yobe to 42.9% in Osun. This was accompanied by a population attributable fraction (PAF) of 116.6%. Tanzania, Cameroon, and Ghana also demonstrated notable disparities, with PAFs exceeding 38%. In contrast, countries such as São Tomé and Príncipe, Lesotho, Eswatini, and Comoros presented minimal spatial inequality. In these countries, the differences between the highest- and lowest-performing regions were less than 6%, and the PAFs were less than 7%. The persistence of wide disparities in EBF in most of the countries points to structural and contextual limitations [25]. For example, health system factors, coverage of baby-friendly hospital initiatives, the availability of skilled lactation support, and the integration of breastfeeding counselling into antenatal and postnatal care may differ significantly between urban and rural regions [20]. Previous studies have noted that areas with greater health service penetration and stronger maternal and child health infrastructure tend to achieve greater implementation of EBF [24]. Conversely, limited health facility access, community outreach, and inconsistent counselling undermine early initiation and maintenance of EBF [1]. Moreover, socioeconomic and educational limitations may further compound these disparities. Numerous studies have shown that maternal education strongly predicts both knowledge and practice of EBF [26, 27]. Regions with higher literacy levels and greater access to media-based health information often exhibit stronger adherence to breastfeeding recommendations [26, 27]. In contrast, in low-literacy or resource-poor areas, misinformation, cultural beliefs, and competing childcare demands frequently lead to early introduction of water or other complementary foods [26, 27]. These behavioural deviations are not isolated decisions but reflections of systemic disadvantage [27].

Furthermore, employment and maternity protection policies could also influence the regional differences observed [26]. In contexts where formal employment is concentrated in urban areas with limited workplace support for breastfeeding, working mothers face structural barriers to maintaining exclusivity [27, 28]. Short maternity leave, a lack of lactation rooms, and inflexible work schedules may compel most of these women to introduce other feeds prematurely [28]. In contrast, regions with higher informal employment or extended family support structures may exhibit better EBF continuity, albeit moderated by economic hardship [29]. Such dynamics highlight how socioeconomic structure interacts with maternal autonomy and the policy environment to shape infant feeding practices. In addition to health system and socioeconomic factors, cultural practices and social norms remain critical determinants of regional disparities. In several African countries, early introduction of water or herbal mixtures is a culturally ingrained practice believed to protect infants from thirst or spiritual harm [30]. These beliefs persist despite public health campaigns promoting EBF. In settings where traditional authority structures strongly influence maternal behaviour, health promotion messages may be less effective unless they are integrated within local communication systems [31]. In contrast, in some southern African countries, such as Lesotho and Zambia, community health outreach and peer-support networks may have achieved better cultural alignment with breastfeeding promotion, potentially explaining their higher and more equitable coverage [22]. Community-based health volunteers, peer counsellors, and maternal support groups have proven effective in improving breastfeeding outcomes when implemented consistently [30, 32]. However, the intensity and continuity of such programmes vary widely between and within countries [32]. This variability may partly account for the large subnational inequalities observed in countries such as Ghana and Kenya, where community health programmes operate unevenly across districts [32]. Sustained investment in community-level capacity building, therefore, remains essential to bridging these gaps.

Broader implications for maternal and child health equity

Promoting equitable breastfeeding practices is integral to achieving Sustainable Development Goals (SDGs) 2 and 3, whose emphasis includes ending hunger and ensuring health and well-being. The spatial inequalities observed in this study align with the broader pattern of health inequities across Africa, where geographic location continues to predict maternal and child health outcomes. This study demonstrates that inequalities in EBF move beyond an issue of access to an uneven distribution of health-promoting environments. To reduce subnational disparities, national governments must adopt regionally differentiated strategies that address both structural and behavioural determinants. This includes integrating equity indicators into national breastfeeding monitoring systems to enable real-time identification of lagging regions. Second, decentralised action plans should empower local health authorities to design culturally appropriate interventions that reflect regional realities. In low-performing areas, investments should prioritise the training of community health workers, the expansion of postnatal counselling, and the enforcement of maternity protection legislation. Equally important is the need to address the structural factors that shape breastfeeding choices. Policies should ensure that women, especially those in informal employment, are protected through social schemes that guarantee income security and flexibility for EBF. In addition, strengthening mass media and community communication strategies tailored to local languages and beliefs could help counter persistent misconceptions. Finally, sustained political commitment, consistent programme financing, and strong coordination between national and subnational health systems are crucial for achieving equitable outcomes.

Study strengths, limitations, and future directions

A key strength of this study is the inclusion of multi-country, harmonised data, which permits direct cross-country comparability of EBF estimates. The application of standardised inequality metrics enhances interpretability and provides quantifiable policy targets. Nonetheless, some limitations warrant consideration. The reliance on secondary data from 2019 means that recent changes in breastfeeding promotion efforts may not have been captured. These data, while harmonised for comparability, may differ slightly from country-specific survey estimates and are subject to inherent modelling uncertainties. Secondly, because the analysis was ecological and cross-sectional, associations observed between geographic location and EBF cannot be interpreted causally. Similarly, subnational aggregation may mask intra-regional heterogeneity, particularly in large countries with wide social and economic variation. Importantly, the analysis included only 18 African countries for which comparable subnational data were available in the HEAT 2024 update. Consequently, the findings may not fully represent the African continent as a whole, and selection bias is possible if countries with available data systematically differ from those without such data. The results should therefore be interpreted as illustrative of regional patterns rather than continent-wide estimates. Also, EBF estimates were based on 24-hour recall and therefore represent current-status feeding rather than exclusivity from birth. This may overestimate true adherence to exclusive breastfeeding, particularly in populations with fluctuating feeding practices. Despite these limitations, the findings provide a baseline for monitoring geographic progress in breastfeeding equity. Notably, the findings of this study reflect patterns only within the 18 included countries. As these countries are geographically clustered and do not evenly represent the entire continent, caution is needed when extrapolating the results to Africa as a whole. Future studies should extend this analysis via longitudinal or geospatial modelling to explore temporal trends and spatial clustering. Integrating contextual variables such as maternal education, healthcare access, and policy enforcement indices would help disentangle the structural drivers of inequality. Moreover, qualitative research could illuminate how cultural narratives and maternal decision-making processes interact with geographic context to shape breastfeeding behaviour.

Conclusion

This study provides a comparative assessment of geographic patterns and subnational inequalities in exclusive breastfeeding (EBF) among infants under six months of age across 18 selected African countries. While some countries, notably São Tomé and Príncipe, Lesotho, and Zambia, demonstrated relatively high and equitable EBF coverage, substantial disparities persisted in many others, including Nigeria, Cameroon, and Côte d’Ivoire. The persistence of wide subnational gaps highlights the continued influence of geographic context on maternal and child health outcomes across the continent. Beyond individual behaviours and service-level factors, the observed patterns suggest that EBF practices are shaped by broader structural, socioeconomic, and policy environments that could either enable or constrain mothers’ ability to breastfeed exclusively. Although improvements in awareness and health promotion remain important, these efforts alone are insufficient to achieve equitable coverage. Therefore, strengthening health systems, enforcing maternity protection policies, and implementing culturally responsive, community-based support mechanisms are likely to be critical for reducing persistent spatial inequalities. Importantly, countries that have achieved more uniform coverage of EBF illustrate that equitable progress is attainable when political commitment, programme continuity, and local ownership are aligned. Closing the remaining geographic gaps in EBF coverage will therefore be essential for accelerating progress towards the World Health Organization (WHO) global nutrition target of 70% EBF by 2030 and for ensuring that all infants, regardless of place of birth, have an equal opportunity to benefit from the protective effects of EBF.

Abbreviations

ANC

Antenatal Care

CI

Confidence Interval

D

Difference

HEAT

Health Equity Assessment Toolkit

EBF

Exclusive Breastfeeding

PAF

Population Attributable Fraction

PAR

Population Attributable Risk

R

Ratio

SDG

Sustainable Development Goal

WHO

World Health Organization

Author contributions

DB conceived and designed the study. DB performed the formal analysis, produced visuals, and interpreted the data. DB wrote the first draft, reviewed, and approved the final manuscript.

Funding

This study received no funding.

Data availability

The dataset used can be accessed at https://whoequity-heat-1.share.connect.posit.cloud/#

Declarations

Ethical approval

This study used publicly available, de-identified, aggregated secondary data obtained from the Institute for Health Metrics and Evaluation (IHME) through the World Health Organization Health Equity Assessment Toolkit (HEAT). No individual-level data were collected or analysed. Consequently, ethical approval and informed consent were not required for this study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.