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Barriers to healthcare access: a multilevel analysis of individual- and community-level factors affecting female youths’ access to healthcare services in Senegal

BMC Health Services Research volume 25, Article number: 607 (2025) Cite this article

Abstract

Introduction

Despite the importance of preventive and curative healthcare use, female youths show a lower likelihood of usage. Factors such as language barriers, autonomy, household economic status, residence, and the education levels of individuals and their spouses influence this dynamic, but with limited evidence from Senegal. Thus, this study explores the magnitude and factors influencing healthcare access among female youths in Senegal.

Methods

This study used data from the 2023 Senegal Demographic and Health Survey (weighted sample size = 7,107). Multilevel logistic regression was used to test both individual and community-level factors associated with the outcome variable, barriers to accessing healthcare services. Adjusted odds ratios (AORs) with 95% confidence intervals (95% CI) were calculated to identify significant associations.

Result

The overall prevalence of barriers to accessing healthcare services among female youths was 69.40%. After adjusting for other variables in the final model, it was found that female youths who had no formal education (AOR = 2.11), primary education (AOR = 1.98), secondary education (AOR = 1.54), no health insurance coverage (AOR = 1.42), lived in poor households (AOR = 2.77), unmarried (AOR = 1.47), or lived in communities with high poverty levels (AOR = 1.87) faced significantly greater barriers to accessing healthcare.

Conclusion

To improve healthcare access for female youth in Senegal, targeted strategies must prioritize advancing educational opportunities, fostering economic empowerment, and expanding health insurance coverage. Special emphasis should be placed on addressing the unique challenges faced by unmarried female youth through tailored support programs. Furthermore, community-wide interventions to reduce poverty and enhance overall socioeconomic conditions are essential for creating a sustainable and equitable healthcare environment.

Peer Review reports

Introduction

The World Health Organization (WHO) states that all citizens have a fundamental right to healthcare services, which nations are responsible for ensuring are accessible and timely [1]. A person's overall health, including their physical, mental, and social well-being, is influenced by their access to healthcare [2]. While access to healthcare is a fundamental determinant of health, it does not guarantee utilization or positive outcomes. Individual agency, cultural beliefs, and systemic inefficiencies may prevent even available services from being used effectively [3]. The ability of an individual to access healthcare services affects both the course of treatment and outcomes of a disease. Barriers to accessing healthcare services significantly impact an individual’s quality of life, as well as their physical and mental health [4].

Health disparities exist across various dimensions, including national, social, and geographical lines [5]. For instance, rural populations often experience poorer health outcomes than their urban counterparts due to inadequate healthcare infrastructure [6]. Within societies, marginalized groups such as ethnic minorities and low-income communities face disparities in healthcare access, leading to increased prevalence of preventable diseases [5]. These broad disparities extend to sex-based health differences, where biological, social, and economic factors contribute to varied health risks and outcomes between men and women [7].

In sub-Saharan Africa (SSA), gender-based health disparities are evident in the prevalence of maternal mortality, complications during childbirth, and limited access to reproductive healthcare services [8]. Women are also more likely to be affected by HIV due to biological susceptibility and socio-economic vulnerabilities [6]. Furthermore, societal norms often limit women’s access to healthcare, as they may require spousal consent for medical consultations or prioritize family needs over personal health [9]. Addressing these sex-based disparities requires targeted interventions that consider both medical and socio-cultural determinants of health.

The Sustainable Development Goals (SDGs) emphasize universal health coverage and equitable healthcare access, yet disparities remain in how health initiatives are implemented [10]. In many regions, healthcare interventions predominantly focus on highly vulnerable groups such as children, pregnant women, and the elderly, sometimes neglecting youth populations [11]. While childhood immunization programs and maternal health initiatives receive substantial attention, adolescents and young adults often lack tailored health programs addressing their unique risks and behaviors [11]. This oversight is concerning, as youth are particularly vulnerable to mental health disorders, substance abuse, and sexually transmitted infections [12]. Recognizing and addressing these gaps is critical to achieving comprehensive and inclusive health coverage.

In SSA, adolescent and youth girls aged 15–24 face numerous sexual and reproductive health challenges, such as a heightened risk of acquiring HIV and other sexually transmitted infections, unintended and unwanted pregnancies, and intimate partner violence [13, 14]. Additionally, substance abuse, including alcohol and drug consumption, poses significant health risks among young people in this age group [15]. Despite these challenges, Studies indicate that healthcare utilization among youths in SSA is low, with rates as low as 20% in some settings and up to 50% in others [16].

Senegal, a Sub-Saharan African country, has experienced moderate economic growth in the twenty-first century [17]. However, it faces high informality, a relatively low employment-to-population ratio, and significant gender disparities [18]. The employment-to-population ratio for females is more than twenty-five percentage points lower than that of males. Nearly half of all young Senegalese women aged 15 to 29 are not in Education, Employment, or Training (NEET), which is more than twice the rate observed among young men [19]. In this country, despite the low utilization of healthcare services among young people, which is 30% [13, 20], there is no national-level evidence on the extent of barriers to healthcare access for female youths or the factors contributing to these barriers. Thus, this study examines healthcare access barriers among female youth in Senegal, focusing on the 2023 Senegal Demographic and Health Survey (SDHS). The primary focus was to assess the magnitude of barriers female youths face in accessing healthcare. Additionally, the study explored whether wealth-related inequalities influenced these barriers and examined both individual and community-level factors contributing to healthcare access challenges.

The findings of this study are expected to enhance efforts aimed at reducing barriers to healthcare access by female youth, particularly by advancing educational opportunities, fostering economic empowerment, and expanding health insurance coverage. In addition, this study will help program managers to give special emphasis on addressing the unique challenges faced by unmarried female youth through tailored support programs.

Methods and materials

Data source, sampling technique, and population

The eighth SDHS, which was conducted between January and August 2023, provided the data that we used. A two-stage, stratified cluster sampling technique was used by the SDHS. In the first stage, 400 clusters were selected with probability proportional to their size, where size is the number of households in the enumerator area (EAs). In the second stage, within each of the EAs selected in the first stage, a fixed number of 22 households were systematically selected with equal probability from newly established lists created at the time of enumeration.

Among the 400 selected EAs, 186 were in urban areas and 214 in rural areas. A total of 8,800 households were selected, comprising 4,092 in urban areas and 4,708 in rural areas. For this study, we used the women’s data (IR) file, resulting in an unweighted sample size of 7,265 female youth aged 15–24 years.

Variables of study

Outcome variable

In this study, the outcome variable, barriers to accessing healthcare, is constructed as a composite measure based on the DHS- 8 guidelines, categorized as "Yes" if the respondent reports experiencing at least one of the following challenges—getting permission to seek treatment, obtaining money for treatment, distance to the health facility, or not wanting to go alone—and "No" if none of these challenges are reported [21, 22].

Independent variables

The independent variables in this study include individual-level factors such as age (categorized into 15–19 and 20–24), educational level (classified as no formal education, primary, secondary, and higher), occupation (divided into not working and working), wealth index (grouped into "poor," combining the "poorest" and "poorer" categories; "middle," which remains unchanged; and "rich," combining the "richer" and "richest" categories) [23], health insurance coverage (no or yes), sex of household head (male or female), current marital status (including "single" for those never in union, "married" for those currently married or living with a partner, and "ever married" for those widowed, divorced, or separated), and religion (Islamic, Christian, or Animist).

Community-level variables include residence (urban or rural), media exposure (no or yes, with "yes" indicating exposure to at least one of three sources: watching television, listening to the radio, or reading a newspaper) [24], Region (the geographical region where the respondent resides, categorized based on Senegal's 14 administrative regions). These regions are further grouped according to the Human Development Index (HDI). Regions with a medium HDI include Dakar, Ziguinchor, and Thiès, while those with a low HDI are Saint-Louis, Tambacoundain each Louga, Fatick, Kolda, Matam, Kaffrine, Kédougou, Sédhiou, and Diourbel [25]. Community-level Poverty: Clusters were evaluated using aggregated poverty measures. Clusters with poverty levels above the median, categorized as "poor" or "poorest," were classified as having a "high poverty level” [26].

Data management and analysis

The outcome and independent variables were extracted from the Individual Recode (IR) dataset. Data extraction, coding, and analysis were conducted using Stata version 17, applying weighted data to ensure representativeness. The individual weight for women (v005) was used to adjust for selection probabilities at both the household and individual levels, accounting for response rate differences. A new variable, wt., was created by scaling v005 (dividing by 1,000,000) to manage large numbers while preserving proportionality for accurate analysis [24]. Weighted analyses accounted for unequal selection probabilities between different categories of respondents and non-response, according to DHS recommendations.

Multilevel analysis

Given the shared traits of young women within clusters, we used a mixed-effects logistic regression model. This model incorporates fixed effects for both individual and community-level factors, along with a random effect to capture variations between clusters. Each community has its own intercept, enabling us to analyze barriers to healthcare access while accounting for differences within clusters [27].

To account for the hierarchical nature of the SDHS data, a mixed-effects model with a cluster-level random intercept was employed to evaluate the clustering effect of barriers to healthcare access. Random effect parameters were used to assess the variability of barriers across different communities, analyzed using the Intra-class Correlation Coefficient (ICC), median odds ratio (MOR), and proportional change in variance (PCV) [24]. The model’s fit was evaluated using deviance, as well as the largest log-likelihood ratio test and the lowest Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The variance inflation factor (VIF) was utilized to assess multicollinearity among the independent variables.

The mixed-effects logistic regression model was utilized to explore the relationship between barriers to healthcare access and explanatory variables at both individual and community levels. Variables with a p-value < 0.25 in bivariate analysis were included in the multivariable analysis. The results were expressed as adjusted odds ratios (AOR) with 95% confidence intervals (CI), with p-values < 0.05 considered statistically significant.

Four models were constructed: the null model (including only the outcome variable), Model One (including individual-level variables), Model Two (focusing on community-level variables), and Model Three (integrating both levels).

Ethics considerations

Ethical approval and participant consent were not required for this study as it involved the secondary analysis of publicly accessible survey data from the DHS Program. Permission to download and use the data for this research was obtained from the DHS Program website (https://dhsprogram.com/Data/terms-of-use.cfm). The datasets do not include any personal identifiers such as household addresses or individual names, ensuring the privacy and anonymity of participants.

Results

Sociology-demographic characteristics of the participants

A total of 7,107 female youths aged 15–24 years were included in the final analysis. The mean age of the participants was 19.21 years, with a standard deviation of 0.03 years. Over one-third (34.60%) came from poor families. The largest proportion (54.55%) was in the 15–19 age group, and nearly 61.48% were single. Approximately 53.42% had achieved secondary education or higher. Most participants (88.95%) had media exposure, while 23.54% were either unemployed or not currently employed. The majority (93.90%) belonged to households without health insurance coverage, and about 70.07% were from male-headed households. Regarding residence and religion, 51.44% lived in urban areas, and 96.77% were Muslim. Regionally, 23.88% of the respondents were from Dakar (Table 1).

Table 1 Socio-demographic characteristics of female youths in Senegal (N = 7107)
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Magnitude of barriers to accessing healthcare

The prevalence of barriers to healthcare access was 69.40% (95% CI: 68.32 to 70.47). The most frequently cited challenges were getting money for treatment (60.79%) and the distance to healthcare facilities (35.60%). The prevalence of barriers to accessing health care was highest among female youth in the Matam (84.39%), in the Tambacounda (81.99%), and in the Saint-Louis (76.80%) regions (Fig. 1).

Fig. 1
figure 1

Magnitude of barriers of health care access among female youths in Senegal across different regions, SDHS 2023

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Results of the random effect analysis and model selection

This study utilized Intra-class Correlation Coefficient (ICC), Median Odds Ratio (MOR), and Proportion of Variance Explained (PCV) to assess the random-effects model. Community-level variability was evaluated using both ICC and MOR. The ICC in the null model was 23.00%, indicating that 23.00% of the total variability in barriers to healthcare access levels among female youth was attributable to differences between clusters. In comparison, the remaining 77.00% was due to individual differences. Furthermore, the highest MOR value of 2.56 in the null model supported the presence of significant clustering of barriers to barriers to healthcare access among these youths. Additionally, a PCV value of (0.1785) in the final model (model III) indicated that both individual and community-level factors explained 17.85% of the variation in barriers to barriers to healthcare access among these populations. The final model, which incorporated both individual and community-level variables, was selected as the best-fit model based on its lowest deviance value (8241.469). This model was used to identify significant factors associated with barriers to healthcare access among female youth in Senegal (Table 2).

Table 2 Random effect and model fitness test result in the adjusted multilevel regression model
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Mixed effect analysis of factors associated with barriers to health care access

In the final multivariable multilevel logistic regression model, both individual- and community-level factors were significantly associated with barriers to healthcare access. Individual-level variables, including educational status, wealth index, health insurance coverage, and marital status, along with community-level variables such as community poverty, were found to influence healthcare access.

Youths with no formal education, primary education, and secondary education had 2.11 times (AOR = 2.11, 95% CI: 1.48–3.03), 1.98 times (AOR = 1.98, 95% CI: 1.38–2.84), and 1.54 times (AOR = 1.54, 95% CI: 1.10–2.14) the odds of encountering barriers to healthcare access compared to those with higher education, respectively. Similarly, youths from poor and middle-income families had 2.27 times (AOR = 2.27, 95% CI: 1.82–2.83) and 1.47 times (AOR = 1.47, 95% CI: 1.14–1.77) greater odds of facing healthcare access barriers compared to those from wealthier families.

Regarding marital status, single youths had 1.47 times (AOR = 1.47, 95% CI: 1.27–1.69) the odds of experiencing barriers to healthcare access compared to their married counterparts. Youths without health insurance had 1.42 times (AOR = 1.42, 95% CI: 1.14–1.77) the odds of encountering barriers compared to those with health insurance.

At the community level, youths living in high-poverty communities had 1.87 times (AOR = 1.87, 95% CI: 1.26–2.77) the odds of experiencing barriers to healthcare access compared to those in lower-poverty communities (Table 3).

Table 3 Mixed effect analysis of factors associated with barriers to health care access among female youths in Senegal, SDHS 2022/23
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Discussion

This study aimed to assess the prevalence and determinants of barriers to healthcare access among female youths in Senegal. The barrier to healthcare access is identified when any of the following challenges arise: difficulty in securing enough money to pay for healthcare services, the physical distance to the nearest health facility, the need for permission to consult a healthcare provider, or concerns about visiting a healthcare facility alone. The most cited barriers are financial constraints in obtaining treatment and the distance to healthcare facilities. The findings indicated that the overall prevalence of barriers to healthcare access among female youths was 69.40% (95% CI: 68.32 to 70.47). The study utilized the latest nationally representative SDHS data, collected through standardized methods, resulting in a robust and generalizable data set. The outcome variable, barriers to healthcare access, was assessed using self-reported data, which is subject to recall bias and social desirability bias. Respondents may have underreported or overreported certain barriers, particularly those influenced by cultural stigma, such as the need for permission to seek healthcare. These biases could affect the accuracy of the findings, potentially leading to an underestimation or overestimation of specific barriers. To minimize these limitations, the study ensured confidentiality, employed standardized survey techniques, and framed questions in a neutral manner. However, results should be interpreted with caution, considering the inherent subjectivity of self-reported data.

The data on barriers to accessing healthcare, specifically among female youth, is currently limited, which constrains the ability to make comprehensive comparisons across different studies and regions. In this study, the prevalence of barriers to healthcare access was higher than the prevalence reported in the only comparable study available from Ethiopia, which recorded a prevalence of 61.3% [28]. The higher prevalence in Senegal compared to Ethiopia may be due to the lack of youth-focused policies, particularly for young women [29]. On top of that, Senegal does not sufficiently prioritize sexual and reproductive health access, lacks a nationwide youth-focused initiative like Ethiopia’s Health Extension Worker (HEW) program, and has fewer rural clinics, making access difficult [30]. Additionally, high out-of-pocket costs for healthcare in Senegal, despite universal health coverage efforts, contrast with Ethiopia’s more subsidized system [31]. The scarcity of studies focusing on this specific population group makes it challenging to contextualize the findings more broadly. Consequently, the higher prevalence observed in our study highlights the need for further research to understand the factors contributing to these barriers and to identify potential regional or demographic variations.

In this study, the odds of barriers to access healthcare were 2.11, 1.98, and 1.54 times more likely among female youths who had no formal education, primary education, and secondary education compared to those who had higher education. This finding is supported by studies done in Benin [32], South Africa [33], East Africa [34], and Ethiopia [28]. A possible reason for this finding could be that a higher educational status may improve awareness and promote increased health-seeking behavior [35]. Additionally, education plays a key role in enhancing employment opportunities, improving income for individuals and households, and contributing to national economic growth, all of which can, in turn, improve access to healthcare services [36, 37]. On the other hand, Low health literacy and limited formal education in poorer communities undermine adolescents'confidence (self-efficacy) to seek care, as they may misinterpret symptoms or underestimate health risks [38].

This study also revealed that youths from the poor and middle-wealth classes faced greater barriers to accessing healthcare compared to those from the lowest-wealth class. This finding aligns with studies conducted in Tanzania [39], SSA [40], and Ethiopia [35]. A possible explanation for this could be that a higher wealth index might alleviate the financial burden of accessing healthcare [41, 42]. Financial capacity can influence the accessibility of health services since both direct costs (such as payments for medications and services) and indirect costs (like transportation expenses and lost income from unpaid work) can hinder access [43]. Most importantly poorest class requires individuals to spend their income on basic needs, such as food, and healthcare costs may therefore be less likely to be affordable [44].

Marital status has been found to significantly influence access to healthcare services, with unmarried (single) youths reporting barriers to access healthcare compared to their married counterparts. This may be attributed to the "spare capacity" within marriage, where responsibilities and tasks are shared, allowing more time, energy, and resources to be devoted to healthcare needs [45]. Additionally, marriage facilitates resource allocation and investment on a mutual basis [46]. The concept of "marriage selection" suggests that individuals who choose to marry often possess certain unseen traits that positively influence healthcare access, utilization, and outcomes [46,47,48]. Unmarried women, on the other hand, may face fewer opportunities to access resources such as health insurance and disposable income, both of which impact their ability to obtain and use healthcare services [49, 50]. Studies indicate that being married is associated with better health outcomes [51,52,53], which may be linked to improved access and utilization of healthcare. We also identified that female youths who had no health insurance coverage face greater barriers to accessing healthcare compared to those from who had health insurance coverage. Beyond its limited population coverage, Senegal's health insurance system exhibits structural limitations that create disproportionate barriers for young women, especially those employed in the informal sector or from low-income households [54]. Similar findings were reported in a study conducted Tanzania [55] and Ghana [56]. This could be due to the fact that having health insurance provides individuals with greater confidence in accessing a broad range of services. It allows for more flexibility in choosing where and when to seek healthcare, without fear of financial burden, as the costs are covered by insurance.

Among the community variables we examined, media exposure, residence, and region showed no significant association with barriers to healthcare access for young females. This may be attributed to Senegal’s Universal Health Coverage (UHC) policy and community-based health initiatives, which help mitigate disparities. The UHC strategy, particularly through the community-based health insurance schemes, aims to enhance financial protection and improve access, especially in rural areas [57]. Additionally, the presence of urban healthcare infrastructure, including regional hospitals and health centers, may help bridge the gap between urban and rural residents. Moreover, health promotion campaigns led by the Ministry of Health, in collaboration with international organizations, likely play a role in raising awareness and minimizing the impact of media exposure disparities on healthcare access [58].

The only community factor found to influence healthcare access was the overall poverty level within a community. A plausible explanation is that individuals in impoverished areas often struggle with financial constraints, making it difficult to afford healthcare services, medications, and transportation to medical facilities. Additionally, these communities may lack adequate healthcare infrastructure, further limiting access [59].

The findings inform strategies to improve healthcare access for female youths. Priority actions include enhancing education, financial independence, and rural healthcare infrastructure while addressing transportation challenges. Community-based solutions tailored to local socio-economic and cultural contexts are crucial. Future research should incorporate mixed methods approaches to gain a deeper understanding of healthcare access barriers among youth in Senegal. While longitudinal studies can help establish causal relationships, qualitative research—such as in-depth interviews and focus group discussions—could explore youth perceptions of healthcare services, provider challenges, and the influence of social and cultural factors. Combining quantitative data with qualitative insights would provide a more comprehensive picture of the structural and individual barriers affecting healthcare access.

Strengths and limitations

The main strengths of this study are its use of a large, representative dataset collected by trained professionals using validated questionnaires, making the findings generalizable across the country. Additionally, multilevel modeling was employed to account for the hierarchical nature of the data, providing reliable estimates. However, two limitations should be noted: the cross-sectional design prevents establishing cause-and-effect relationships, and two important factors—attitude and service quality—were excluded, as they require qualitative studies for proper analysis.

Conclusion

A significant proportion of female youths encountered barriers to accessing healthcare, with financial constraints in obtaining treatment and the distance to healthcare facilities being the most frequently cited challenges. The education level, economic status, marital status, and health insurance coverage of female youths were significant individual-level factors influencing healthcare access. At the community level, poverty was the only significant factor identified. Policies should prioritize empowering youths through education and economic opportunities, with special attention to unmarried female youths. Additionally, female youths should be encouraged to obtain health insurance. The Senegalese government should also focus on reducing community poverty by ensuring access to national education.

Data availability

The datasets used and/or analyzed for this study are available from the Demographic and Health Surveys https://dhsprogram.com/Data/terms-of-use.cfm.

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Acknowledgements

HAWe are grateful to the DHS programmers for letting us use the relevant DHS data in this study.

Funding

No Funding from external sources.

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Authors and Affiliations

  1. Department of Human Anatomy, School of Medicine, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia

    Hailu Aragie & Habtu Kifle Negash

  2. Department of Epidemiology, Institute of Public Health, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia

    Habtu Kifle Negash & Mihret Getnet

  3. Department of Human Physiology, School of Medicine, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia

    Mihret Getnet, Winta Tesfaye & Yibeltal Yismaw Gela

  4. Department of Medical Biochemistry, School of Medicine, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia

    Hiwot Tezera Endale

  5. Department of Medical Nursing, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia

    Tseganesh Asefa

  6. Department of Gynecology and Obstetrics, School of Medicine, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia

    Maru Mandefro Woldeyes

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  1. Hailu Aragie
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Contributions

HA., HKN., MG., WT., YYG., TA., M.M.W., and HTE. Participated in conceptualization, formal analysis, investigation, methodology, supervision, visualization, writing-original draft, writing-review and editing, and approving the final draft. All authors read and approved the manuscript.

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Correspondence to Hailu Aragie.

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Ethics approval and consent to participate

Ethical approval and participant consent were not required for this study as it involved the secondary analysis of publicly accessible survey data from the DHS Program. Permission to download and use the data for this research was obtained from the DHS Program website (https://dhsprogram.com/Data/terms-of-use.cfm). The datasets do not include any personal identifiers such as household addresses or individual names, ensuring the privacy and anonymity of participants.

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Aragie, H., Negash, H.K., Getnet, M. et al. Barriers to healthcare access: a multilevel analysis of individual- and community-level factors affecting female youths’ access to healthcare services in Senegal. BMC Health Serv Res 25, 607 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12913-025-12761-2

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BMC Health Services Research

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