Wealth-based inequalities in the uptake of three or more doses of intermittent preventive treatment in pregnancy in West Africa, 2015–2021

Abstract

Background

Anaemia in pregnancy remains a major public health challenge in sub-Saharan Africa, contributing to adverse birth outcomes, including low birth weight and neonatal mortality. The World Health Organization (WHO) recommends the uptake of intermittent preventive treatment during pregnancy with at least three doses of sulfadoxine-pyrimethamine (IPTp-SP3) to reduce these adverse outcomes. Achieving equitable distribution of IPTp-SP3 is essential for advancing Sustainable Development Goal 3 (SDG3), which aims to achieve universal health coverage and equitable access to healthcare services for all men and women. However, continued disparities in the uptake of IPTp3 across socioeconomic groups are evident in many African countries. This study, therefore, investigates wealth-based inequalities in IPTp-SP3 coverage across 15 West African countries.

Methods

Using the WHO Health Equity Assessment Toolkit (HEAT), the study analysed secondary data drawn from the Demographic and Health Surveys (DHS), Malaria Indicator Surveys (MIS) and Multiple Indicator Cluster Surveys (MICS) conducted from 2015 to 2021, across 15 West African countries. Four measures of inequalities: Absolute Difference (D), Prevalence Ratio(R), Population Attributable Risk(PAR) and Population Attributable Fraction(PAF) were used to assess wealth-related inequalities in IPTp-SP3 coverage.

Results

The lowest IPTp-SP3 coverage, 11.2% was recorded in Mauritania, whilst Burkina Faso recorded the highest coverage of 57.7%. The results revealed substantial wealth-related inequalities. IPTp-SP3 coverage was high among the population's richest quintiles in Guinea (D = 30.3%), Togo (D = 27.6%) and Benin (D = 17.6%). Paradoxically, in Liberia (D = − 4.5%), Nigeria (D = − 4.4%), and Sierra Leone (D = − 3.1%), the poorest quintiles experience the highest IPTp-SP3 coverage compared to the richest quintiles. Countries with the greatest potential national increase in IPTp-SP3 coverage if the poorer quintiles had the same level of access as the richest were Togo (17.3), Guinea (17.2) and Senegal (6.3) percentage points. However, near-equitable access to IPTp-SP3 was observed in Liberia, Nigeria and Sierra Leone.

Conclusion

Wealth-based inequalities continue to hinder IPTp-SP3 uptake in West Africa. Addressing these disparities require targeted equity-driven strategies to improve coverage among pregnant women and towards achieving the objectives of SDG 3.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-025-05669-z.

Background

Malaria remains a critical public health challenge in West Africa, with 15 endemic countries in 2023, and Plasmodium falciparum responsible for nearly all transmissions, except in Cabo Verde, which has eliminated malaria [1]. The region accounted for an estimated 124 million malaria cases and 311,000 deaths in 2023, with Nigeria alone contributing 55% of cases [1]. Children under five bear the greatest burden, accounting for 67% of deaths, while pregnant women remain highly vulnerable due to immunological changes that increase the risk of severe disease and adverse outcomes such as low birth weight and stillbirth [1, 2].

Interventions on vector control have been through mass distribution of insecticide-treated nets (ITNs), with over 72 million nets distributed in 2023 and seasonal malaria chemoprevention (SMC) targeting children. The RTS,S/AS01 malaria vaccine has been introduced subnationally in seven countries, including Ghana and Burkina Faso, further enhancing prevention efforts [3]. Intermittent preventive treatment in pregnancy with sulfadoxine-pyrimethamine (IPTp-SP3) is also implemented in 14 countries [1, 3]. IPTp-SP3 is administered as a full therapeutic course starting as early as the second trimester and continued at monthly intervals during routine antenatal care (ANC) visits, regardless of malaria infection status [3–5]. This strategy significantly reduces placental parasitaemia, maternal anaemia, preterm delivery, and low birth weight [5].

In 2012, the WHO updated its policy, increasing the recommended minimum number of IPTp-SP3 doses from two to at least three, based on evidence showing that three or more doses yield improved maternal and neonatal outcomes, including higher birth weights and lower risk of low birth weight compared to the two-dose regimen [4, 6–8] as shown in supplementary file 1. Despite this recommendation, IPTp-SP3 uptake is suboptimal across many West African countries with variations between countries and socio-economic groups [7, 9–11]. A similar study conducted in eight African countries reported 29.5% average IPTp-SP3 uptake, with the highest in Ghana (60%), Kenya (37%) and Sierra Leone (31%). Also, women from middle to richest households, and those with lower levels of education, had higher uptake of IPTp-SP3 [12]. Contrary to the finding that lower education status is associated with higher IPTp-SP3 uptake, several studies across different African countries have shown that higher maternal education is positively associated with greater adherence to the recommended three or more doses of IPTp-SP3 [13–16].

Several factors affect the uptake of IPTp-SP3 across sub-Saharan Africa. There are unclear or inconsistent national health policies and implementation guidelines, frequent stockouts of SP, and the imposition of user fees [12, 17], while at the facility level, there is poor organization of care, suboptimal service quality, and healthcare providers’ confusion regarding the correct timing and dosing of IPTp-SP3 [18]. Also, ANC attendance, often shaped by socio-economic factors and geographic accessibility, limits women’s opportunities to receive the recommended IPTp-SP3 doses [19, 20]. Individual-level determinants such as maternal health education, awareness of malaria and IPTp-SP3 benefits, household wealth, parity, and the number and timing of ANC visits consistently influence IPTp-SP3 uptake with varying effects across different contexts [21–24].

Wealth-related disparities are among the most entrenched barriers to equitable maternal health service delivery [12]. Therefore, understanding current wealth-related inequalities in the IPTp-SP3 uptake is essential for informing effective national and regional strategies aimed at scaling up coverage and reducing the malaria burden among pregnant women in high-transmission settings. This study contributes to the body of evidence on maternal malaria and household wealth by analyzing data from 15 West African countries, drawing on recent Demographic and Health Surveys (DHS), Malaria Indicator Surveys (MIS), and Multiple Indicator Cluster Surveys (MICS) conducted between 2015 and 2021. The analysis covers all West African countries except Cabo Verde, which has successfully eliminated malaria since 2023 [1]. Particular emphasis is placed on updated findings and wealth-related inequalities, offering additional evidence into socioeconomic disparities in IPTp-SP3 coverage. This study utilizes the World Health Organization’s Health Equity Assessment Toolkit (HEAT), which provides standardized measures of inequality derived from DHS, MICS, and MIS. The HEAT toolkit enables consistent cross-country comparisons and facilitates policy-relevant interpretation of health equity indicators [25, 26].

Methods

Data source

Data from 15 West Africa countries: Benin, Burkina Faso, Côte d’Ivoire, The Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Senegal, Sierra Leone, and Togo were obtained from the WHO Global Health Observatory’s Health Equity Monitor. Which compiles health inequality data from nationally representative household surveys including the DHS, Malaria MIS, and MICS. These data are harmonized and integrated into the WHO HEAT, (Version 6.0) [25], a specialized software tool for analysing health inequalities (see details here https://whoequity-heat-1.share.connect.posit.cloud/).

To account for the complex survey design of DHS, MIS, and MICS, HEAT internally applies survey weights, clustering, and stratification. Survey weights adjust for unequal probabilities of selection and non-response, ensuring nationally representative estimates. Clustering at the primary sampling unit and stratification by survey-defined strata are incorporated to provide correct variance estimation and confidence intervals. As a result, all coverage estimates and inequality measures generated by HEAT reflect the true population distribution and account for the precision of estimates arising from the survey design [25, 26].

Variables

Outcome variable

The primary outcome indicator was the use of three or more doses of IPTp-SP3, defined as the percentage of women aged 15–49 years with a live birth in the two years preceding the survey who reported receiving at least three doses of IPTp-SP3 during their most recent pregnancy. This measure aligns with the WHO’s updated recommendation for optimal malaria prevention in pregnancy.

Explanatory variable

The explanatory variable of inequality was household wealth status, categorized by five quintiles: poorest, poorer, middle, richer, and richest, based on the DHS/MICS wealth index constructed using principal component analysis of household assets, housing characteristics, and access to basic services.

Data analysis

Data analysis was carried out using the WHO HEAT, supported by Microsoft Excel for data cleaning, organization, and presentation. Four equity summary measures were used to assess wealth-based disparities in the uptake of IPTp-SP3.

First, the Absolute Difference (D) was computed as the percentage point difference in IPTp-SP3 coverage between the richest and poorest wealth quintiles. A positive value of D indicates higher coverage among the richest, while a value of zero reflects equity:

$$\mathit{D}=\text{IPTp}3\text{richest}-\text{IPTp}3\text{poorest}$$

Second, the Prevalence Ratio (R) was calculated by dividing the IPTp3 coverage in the richest quintile by that of the poorest. This relative measure reflects the proportional advantage in IPTp uptake among the wealthiest group. An R value greater than 1 denotes pro-rich inequality, while a value of 1 indicates parity between groups:

$$\text{R}=\frac{\text{IPTp}3\text{richest}}{\text{IPTp}3\text{poorest}}$$

Third, the Population Attributable Risk (PAR) was used to estimate the absolute increase in national (country specific) IPTp-SP3 coverage that would be achieved if all wealth quintiles had the same coverage as the richest group. It reflects the potential gain in coverage, expressed in percentage points.

$$\mathit{P}\mathit{A}\mathit{R}=\text{IPTp}3\text{richest}-\text{IPTp}3\text{national average}$$

Lastly, the Population Attributable Fraction (PAF) was computed to show the proportion of the national IPTp-SP3 coverage gap that could be eliminated by addressing wealth-based inequality. It expresses PAR as a percentage of the coverage level in the richest group, providing a relative perspective on the burden of inequality:

$$\text{PAF}=\left(\frac{\text{PAR}}{\text{IPTp}3\text{national average}}\right)\ast 100$$

All summary measures were generated using HEAT’s in-built functions and interpreted in accordance with WHO guidelines [26]. Higher values of D, R, PAR, or PAF indicate greater inequality in IPTp-SP3 uptake in favour of wealthier groups.

Results

Coverage of IPTp-SP3 by country

Figure 1 shows variations in the average uptake of three or more doses of IPTp-SP3 across the 15 West African countries. IPTp-SP3 coverage was 29. 8% for all the countries. Burkina Faso recorded the highest average coverage at 57.7%, followed closely by Ghana (51.7%), Togo (41.7%), and the Gambia (37.5%). In contrast, the lowest IPTp-SP3 uptake was observed in Mauritania (11.2%), Benin (13.7%), and Nigeria (14.9%), indicating possible gaps in malaria prevention during pregnancy in those countries. In addition, IPTp-SP3 coverage in Côte d’Ivoire was 22.6%, in Senegal (22.0%), and Guinea-Bissau (24.2%). This is also captured in detail in supplementary file 2.

Fig. 1.

Coverage of IPTp-SP3 by country

Wealth-related inequalities in IPTp-SP3 coverage

As shown in Fig. 2 and supplementary file 3, across the 15 West African countries, wealth-related disparities in IPTp-SP3 uptake were evident, though their direction and magnitude varied considerably. Benin, Guinea, Togo and Mauritania had a pro-rich gradient, with coverage increasing in favour of the pro-rich quintiles. Notably, Benin exhibited strong inequality: coverage rose from 5.6% among the poorest to 23.2% among the richest, a more than fourfold difference. A similar pattern was observed in Guinea, where IPTp-SP3 coverage increased from 22.6% (poorest) to 52.9% (richest). In Togo, coverage nearly doubled from 29.5% in the poorest quintile to 60.1% among the richest. Mauritania also showed coverage increasing from 6.3% in the poor quintile to 17.3% in the richest group. Other countries demonstrated flatter gradients. In Mali, coverage ranged modestly from 23.0% in the poorest quintile to 33.5% in the richest. Gambia and Ghana showed minimal gaps between the poorest and richest, suggesting near-equitable distribution. In Ghana, the richest quintile had slightly lower coverage (57.3%) than the fourth quintile (59.5%). A few countries showed inverse patterns from the preceding descriptions. In Liberia, coverage was highest among middle-income groups (28.9%) and lowest among the richest (14.9%). Similarly, in Nigeria, coverage declined from 16.7% (poorest) to 12.3% (richest). In Guinea-Bissau, there was no consistent trend, with coverage peaking in quintile 3 (30.4%) then dropping in higher quintiles.

Fig. 2.

Wealth-Related Inequalities in IPTp-SP3 Coverage in 15 West African Countries

Wealth-related inequalities in IPTp-SP3 coverage: a summary measure analysis

Table 1 shows results from the analysis of wealth-related disparities in IPTp-SP3 coverage using standardized equity summary measures. The absolute difference (D), an absolute measure quantifying the gap in IPTp-SP3 coverage between the richest and poorest quintiles, was most pronounced in Guinea (30.3 percentage points), followed by Togo (27.6), Benin (17.6), and Ghana (13.7). Also, Senegal (11.1) and Mali (10.5) had notable disparities. In contrast, negative D values were observed in Nigeria (− 4.4), Liberia (− 4.5), and Sierra Leone (− 3.1), indicating higher IPTp-SP3 coverage among the poorest quintile.

Table 1.

Wealth-Related Inequalities in IPTp-SP3 Coverage: A Summary Measure Analysis

Country	Survey year	D (%)	R	PAR (%)	PAF
Benin	2017	17.6	4.1	9.6	70
Burkina Faso	2017	2.2	1	1.2	2.1
Côte d'Ivoire	2016	5.8	1.3	2.1	9.3
Gambia	2018	6	1.2	3.1	8.3
Ghana	2018	13.7	1.3	5.6	10.8
Guinea	2018	30.3	2.3	17.2	48.2
Guinea-Bissau	2019	0.4	1	0	0
Liberia	2016	− 4.5	0.8	0	0
Mali	2018	10.5	1.5	5.2	18.5
Mauritania	2015	5.2	1.4	6.1	54.5
Niger	2021	9.1	1.5	2.2	8.9
Nigeria	2017	− 4.4	0.7	0	0
Senegal	2017	11.1	1.6	6.3	28.4
Sierra Leone	2017	− 3.1	0.9	0	0
Togo	2017	27.55	1.95	17.3	43.7

D refers to Difference, R to Ratio, PAR (%) to Population Attributable Risk, and PAF to Population Attributable Fraction

The prevalence ratio (R), a relative measure comparing IPTp-SP3 coverage in the richest quintile to that in the poorest, showed patterns consistent with the absolute differences. The highest R values were observed in Benin (4.1), where coverage among the wealthiest was more than four times that of the poorest. Elevated R-values were also recorded in Guinea (2.3) and Senegal (1.6). Moderate inequalities were evident in Mali and Niger (both 1.5), Mauritania (1.4), and Ghana and Côte d’Ivoire (1.3 each). Countries such as Gambia (1.2) and Guinea-Bissau (1.0) exhibited comparatively lower relative inequality. Conversely, Liberia (0.8), Sierra Leone (0.9), and Nigeria (0.7) had R values below 1.0, indicating relatively higher IPTp-SP3 coverage among the poorest quintiles.

The PAR, which reflects the potential absolute increase in IPTp-SP3 coverage if all wealth quintiles achieved the coverage level of the richest group in each country, was highest in Togo (17.25 percentage points), Guinea (17.2), and Senegal (6.3). Zero PAR values were recorded in Guinea-Bissau, Liberia, Nigeria, and Sierra Leone, indicating no expected gain from equalizing coverage across wealth groups in these countries.

The PAF, expressing the proportion of total shortfall in IPTp-SP3 coverage attributable to wealth-related inequality, was largest in Benin (70.0), followed by Mauritania (54.5), Guinea (48.2), and Togo (43.7). Ghana (10.8), Côte d’Ivoire (9.3), and Gambia (8.3) had comparatively lower PAF values, while Liberia, Nigeria, and Sierra Leone recorded PAF values of zero.

Discussion

The study reveals significant wealth-based disparities in the uptake of IPTp-SP3 across many West African countries, with varying coverage rates, and IPTp-SP3 uptake ranging from as low as 11.2% in Mauritania to 57.7% in Burkina Faso. Yet, women from poorer households consistently have lower coverage compared to their wealthier counterparts. This gap remains far below the Roll Back Malaria (RBM) target of 80% coverage for at least two doses of IPTp-SP3, and consistent with previous studies [23, 28, 29]. Poor coverage of IPTp-SP3 remains a serious concern for malaria in pregnancy prevention programmes led by health Non-Governmental Organizations and governments across sub-Saharan Africa [28]. Despite policy efforts, healthcare systems frequently fail to promote maternal health service utilization due to persistent infrastructural, sociocultural, and financial barriers [30]. Key health system challenges include stockout of sulfadoxine-pyrimethamine (SP), unclear or delayed policy adoption, user fees, and inadequate training of healthcare providers, which lead to missed opportunities for IPTp-SP3 administration during ANC visits [30–32].

Wealth-related disparities in IPTp-SP3 coverage were particularly pronounced in Guinea, Benin, and Togo. Guinea exhibits the highest absolute inequality, indicating that women in the wealthiest quintile are more than twice as likely to receive IPTp-SP3 coverage compared to the poorest [33, 34]. Togo and Benin also show substantial inequalities, reflecting significant relative disparities [3, 36]. These findings are consistent with previous research across sub-Saharan Africa, demonstrating that wealthier women have higher IPTp-SP3 uptake due to better access to antenatal care, fewer financial constraints, and greater health literacy [12, 24, 25]. For example, in Uganda and Tanzania, women living in relatively poorer households were less likely to report taking 2 + doses of IPTp-SP3 [35, 36].

In Liberia, Nigeria, and Sierra Leone, wealth-related disparities in IPTp-SP3 coverage were minimal or even slightly pro-poor. For instance, Nigeria exhibited a negative difference and prevalence ratio, indicating marginally higher IPTp-SP3 coverage among poorer women compared to their wealthier counterparts. This paradoxical finding may have several explanations. First, in countries with relatively weak or unevenly distributed health systems, wealthier women may substitute public ANC services with private or unregulated care providers, where malaria prevention protocols, including IPTp-SP3 administration, are inconsistently implemented or poorly documented [38]. Second, national and donor-supported community outreach interventions may have been more successful in targeting and reaching poorer or rural women through public-sector programmes, thereby narrowing or even reversing traditional pro-rich gradients. Third, differences in data quality and measurement could partly explain these results, particularly if survey respondents misreported IPTp-SP3 doses or if private-sector data were underrepresented in national surveys. These factors collectively suggest that the observed pro-poor patterns may not necessarily reflect genuine equity in malaria prevention coverage but rather structural and systemic differences in service delivery, data capture, and healthcare-seeking behaviour. Understanding these nuances is essential for interpreting wealth-based inequalities and designing context-specific interventions to improve equitable IPTp-SP3 coverage across West African settings [39].

The results suggest that substantial improvements in IPTp-SP3 coverage could be achieved through equity-oriented interventions. PAR estimates indicate that national IPTp-SP3 coverage in countries such as Guinea, Togo, and Senegal could rise considerably if the coverage levels observed among the richest quintile were extended across all socioeconomic groups [35]. Moreover, the PAF illustrates the potential proportion of the coverage shortfall that could be reduced by addressing wealth-related disparities, recognizing that wealth interacts with other structural factors influencing access and utilization [20, 33, 34]. These findings are consistent with evidence showing that community-based delivery approaches and targeted equity interventions effectively increase IPTp-SP3 uptake and reduce socioeconomic gaps in malaria prevention during pregnancy [33, 40, 41]. Given the persistent barriers such as stockout, financial constraints, and limited ANC access, focusing on equity is critical to meeting country and regional malaria prevention targets and improving maternal and neonatal health outcomes [21, 42].

It appears that healthcare systems in West Africa face significant wealth-related inequalities that hinder the optimal coverage and utilization of IPTp-SP3 [43–45]. These disparities pose a major challenge to malaria prevention and elimination efforts, as poorer women consistently experience a lack of access to antenatal care services and IPTp-SP3 [33, 44]. Addressing these structural inequities is essential to achieving equitable maternal health outcomes and advancing malaria control goals in the region.

It is argued that over 90% of malaria cases worldwide likely go unreported [46]. The surveillance and data collection systems are weakest precisely in the regions with the highest malaria burden, particularly in many African countries where reliable data are often lacking [47]. This underreporting stems from limited diagnostic capacity, incomplete case detection, insecurity issues and fragile health information infrastructure in endemic areas [46, 48].

An interesting and policy-relevant pattern emerges from the cross-country comparisons of IPTp-SP3 coverage and wealth-related inequality. Countries with very low coverage (e.g., Mauritania) tended to show low measured inequality, those with moderate coverage (e.g., Benin) often showed large wealth gaps, and countries with high coverage (e.g., Burkina Faso) exhibited relatively small gaps. This pattern is consistent with the inverse-equity hypothesis and an inverted-U (Kuznets-type) relationship between coverage and inequality, whereby new or expanding health interventions are first adopted by the better-off, increasing inequality as coverage rises, before benefits diffuse more broadly and inequalities decline as coverage approaches universality [48].

The inverse-equity dynamic has been observed across a range of maternal and child health services and is discussed extensively in the literature on coverage and equity. It is argued that monitoring coverage by subgroups is essential because national averages can mask divergent subgroup trends and because inequality dynamics may change as programmes scale up [49, 50]. The WHO similarly emphasizes that different phases of service scale-up can be associated with changing inequality patterns and recommends monitoring both absolute and relative measures during expansion to detect and mitigate widening gaps [50]. Empirical work supports this conceptual framing. Analyses across many national surveys have documented increases in absolute inequality during early to intermediate phases of scale-up for services such as institutional delivery and immunization, followed by reductions in inequality as programmes mature and coverage becomes more widespread [50].

These patterns have direct programmatic implications. First, they suggest that scale-up strategies must integrate equity measures from the outset: rapid expansion that neglects targeted outreach may inadvertently widen gaps before they narrow. Second, they underline the need for mixed analytic approaches (e.g., monitoring of both coverage and inequality indices; decomposition and Theil-based analyses where data permit) to identify whether inequality arises primarily from between-group differences or substantial within-group heterogeneity and to inform tailored responses [50, 51].

Strengths and limitations

This study presents a comprehensive regional analysis of wealth-related inequalities in the uptake of intermittent preventive treatment in pregnancy with three or more doses of IPTp-SP3 across 15 West African countries. The analysis employed the WHO HEAT which uses standardized and validated measures of inequality, D, R, PAR, and PAF to ensure comparability across countries.

The study draws on nationally representative datasets between 2015 and 2021, all of which used a consistent two-stage stratified cluster sampling design. To account for this complex survey design, WHO HEAT applies survey weights, clustering, and stratification as specified in the DHS datasets, ensuring that all reported estimates are population-weighted and reflect appropriate design-adjusted variance calculations. This approach maintains the precision and representativeness of national estimates and prevents bias arising from unequal sampling probabilities.

Wealth quintiles were computed using the DHS asset-based index constructed through propensity score matching, allowing a harmonized classification of household socioeconomic status across countries. This methodological consistency enhances internal validity and strengthens cross-country comparability of equity estimates.

A key strength of this study is its regional scope, which provides one of the most extensive and standardized assessments of equity in maternal malaria prevention in West Africa. By focusing on wealth as a core social determinant, it highlights an often underexplored dimension of inequity in IPTp-SP3 uptake. Moreover, the analysis reveals a potential Kuznets-type (inverted-U) relationship between IPTp-SP3 coverage and inequality, where disparities tend to widen at intermediate coverage levels and narrow once services become more universally accessible. This offers novel empirical evidence that supports equity transition theories in public health.

However, several limitations should be acknowledged. First, the reliance on data from 2015–2021 may not fully reflect more recent changes in malaria control policies or service coverage, particularly post–COVID-19. Second, this analysis focused solely on wealth as the equity dimension; other potential drivers such as education, geographic access, and quality of antenatal care were not included due to data limitations. Additionally, interaction effects between wealth and these variables could not be explored, which limits understanding of how multiple vulnerabilities jointly influence IPTp-SP3 uptake.

Fourth, although WHO HEAT provides standardized computation procedures, it does not generate confidence intervals or sensitivity analyses. Consequently, the precision of the estimates cannot be directly tested; nonetheless, the platform’s reliance on complex survey-adjusted weighting ensures robust and comparable national estimates.

Finally, national-level analyses may mask substantial subnational heterogeneity in coverage and inequality. Therefore, results should be interpreted as reflecting overall national trends rather than uniform patterns within countries. The cross-sectional nature of the data further limits causal inference. Unexpected findings, such as slightly pro-poor IPTp-SP3 distribution in Nigeria, Liberia, and Sierra Leone, may reflect substitution of care among wealthier women to private or informal providers, health system constraints, or data quality variations, warranting further investigation through mixed-methods and longitudinal research.

Conclusion

This study highlights wealth-related inequalities in the uptake of IPTp-SP3 across West Africa, with several countries exhibiting pro-rich disparities. While some progress in IPTp-SP3 coverage has been observed, socioeconomic gaps remain, potentially limiting equitable access to malaria prevention in pregnancy. Efforts to reduce these disparities could contribute to improving maternal and neonatal health outcomes and advancing progress toward Sustainable Development Goal 3. Although the analysis is based on data from 2015 to 2021, the findings offer guidance for targeted policies and underscore the importance of updated, disaggregated data to inform future interventions.

Abbreviations

ANC

Antenatal care

DHS

Demographic and Health Survey

HEAT

Health equity assessment toolkit

IPTp

Intermittent preventive treatment in pregnancy

IPTp-SP3

Intermittent preventive treatment in pregnancy with sulfadoxine-pyrimethamine

IPTp3

Three or more doses of intermittent preventive treatment in pregnancy

MICS

Multiple indicator cluster surveys

MIS

Malaria indicator survey

NGO

Non-Governmental Organization

PAR

Population attributable risk

PAF

Population attributable fraction

R

Ratio

RBM

Roll back malaria

D

Difference

SDG

Sustainable Development Goal

SP

Sulfadoxine-pyrimethamine

SSA

Sub-Saharan Africa

WHO

World Health Organization

Author contributions

AI and AS conceived the study. AI and AS wrote the methods section and performed the data analysis. AI, SZ, TJ, and AS were responsible for the initial draft of the manuscript. All the authors reviewed and approved the final version of the manuscript.

Funding

This study received no funding.

Data availability

The dataset used can be accessed at: [https://www.who.int/data/inequality-monitor/data] (https:/www.who.int/data/inequality-monitor/data).

Declarations

Ethics approval and consent to participate

No ethical clearance was sought for this study due to the public availability of the dataset.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.