Introduction

Breast cancer remains a significant health concern worldwide and ranks as one of the leading causes of cancer mortality among women, particularly in low- and middle-income countries [1,2]. Despite the rising incidence of breast cancer, early detection through screening has been largely suboptimal, resulting in late-stage diagnoses and poor outcomes for many affected women [3]. Globally, an estimated 2.3 million women were diagnosed with breast cancer in 2020, leading to approximately 685,000 deaths, with many of these occurring in sub-Saharan Africa where awareness and screening practices are critically low [3,4]. By 2050, new cases and deaths are projected to rise by 38% and 68%, respectively, with low HDI countries being disproportionately affected [5]. This situation underscores the significant challenges faced by low- and middle-income countries (LMICs), driven by disparities in healthcare access and outcomes [6].

Breast cancer is the leading cause of cancer-related deaths in women globally and a significant public health burden in sub-Saharan Africa, which accounts for approximately 15% of all cancer-related mortality [7]. In sub-Saharan Africa, breast, cervical, and prostate cancers dominate the overall cancer burden, with breast cancer accounting for 25% of new cases in women [8,9]. By 2040, breast cancer is expected to result in over 3 million new cases and 1 million deaths annually due to population growth and aging alone [10]. In Africa, breast cancer accounts for 25% of all diagnosed cancers and is responsible for 20% of cancer-related deaths among women. The incidence of breast cancer in Africa is steadily rising and is expected to double by 2050 [11]. In sub-Saharan Africa, breast cancer incidences increased by 247% from 1990 to 2019 [8]. Despite improved survival rates, significant disparities exist between countries due to factors like inadequate early-stage screening, detection, and affordable therapy [12].

Although breast cancer mortality is higher in Africa than in high-income countries, the disease has not been extensively studied in the region [13]. Moreover, the burden of breast cancer in women aged 15–49 is particularly concerning, as this age group is less studied and their health impacts extend to their families and society [1]. Breast cancer is a major global public health issue, especially in low-resource countries. Screening services are effective for early detection [14]. In low-resource settings, the WHO recommends clinical breast examination (CBE) as the most cost-effective screening for women [15]. The study found that breast cancer screening utilization in 14 low-resource countries was 15.41%, with variations of 81.10% in Europe, 18.61% in Asia, 14.30% in the Americans, and 14.29% in Africa [14]. A survey in four sub-Saharan African countries revealed a 12.9% prevalence of breast cancer screening [16]. Another study showed that 18.4% of women in Ghana utilized breast cancer screening services [17]. A study in Tanzania found a 5.2% prevalence of breast cancer screening [18]. Factors associated with screening included age, educational status, residence, marital status, health insurance coverage, wealth index, distance to health facilities, parity, contraceptive use, media exposure, and breast cancer awareness [16,17,19–21]. According to the 2014 DHS, breast cancer screening utilization in Lesotho was 9.73% [3]. So, the utilization of breast cancer screening services is low in many low-resource countries, including Lesotho [3,14]. While breast cancer cannot be entirely prevented, adopting lifestyle changes and early diagnosis significantly reducing incidence and mortality rates. Therefore, screening is crucial for early breast cancer detection and significantly reduces mortality rates [22].

In Lesotho, breast cancer is the second most common cancer among women, with a weak healthcare system and low screening rates [20]. Together, breast and cervical cancers account for approximately 43% of all annual cancer diagnoses in the country [23]. The 2023−24 Lesotho Demographic and Health Survey (DHS) offers a unique opportunity to identify the prevalence and determinants of breast cancer screening in this population. Despite the high mortality rates associated with breast cancer, the prevalence of screening among women of reproductive age in Lesotho remains alarmingly low [20]. Previous research in sub-Saharan Africa has highlighted several key determinants, including education level, age, health insurance coverage, and socioeconomic status [16,24]. Access to healthcare services and health insurance coverage, along with socio-demographic and economic factors, significantly correlate with higher breast cancer screening utilization. Additionally, screening behaviors, prior knowledge, and physician access influence women’s participation in screening services [14].

However, a significant gap exists in the literature regarding the specific context of Lesotho. In this country, breast cancer has become one of the leading causes of morbidity and mortality among women. Despite this, there is a limited understanding of the factors that influence breast cancer screening services for women of reproductive age [20]. Most of the existing studies in Lesotho have focused on factors associated with awareness of breast cancer screening, primarily utilizing data from the 2014 Demographic and Health Survey (DHS) dataset [3,20,25,26]. However, this dataset is now outdated. Updated information based on the newly released Lesotho DHS dataset, analyzed through the lens of the Anderson Behavioral Model, could be instrumental in identifying the factors associated with the utilization of breast cancer screening among women of reproductive age. This study aims to explore these determinants using the Andersen Behavioral Model, which provides a comprehensive framework for understanding health service utilization [24]. The Andersen Behavioral Model was chosen for its relevance in explaining health service utilization, particularly in preventive care such as cancer screening. This model conceptualizes service use as being influenced by three domains: predisposing factors (such as socio demographic traits), enabling factors (including access and resources), and need factors (referring to perceived or actual health status) [27]. It has been extensively applied in studies throughout sub-Saharan Africa and globally to investigate disparities in screening uptake [28–30]. This updated analysis would provide valuable insights for policymakers, enabling them to develop more effective strategies to improve breast cancer screening rates and ultimately enhance women’s health outcomes in Lesotho.

Methods

Results

A total of 6413 weighted reproductive-age women were included in this study. Among the respondents, 36.78% of women were in the age group 15–24 years, and 57.41% had secondary-level education. Additionally, 50.35% of the reproductive-age women were currently unmarried. More than half of the participants (54.50%) lived in rural areas, and 56.96% of the households were headed by males. More than two-thirds (67.38%) of participants visited healthcare facilities in the last 12 months, and more than three-fourths (75.86%) of participants did not consider distance to a healthcare facility a big problem. A significant portion of participants did not have health insurance (95.78%). Nearly half (49.80%) of reproductive-age women reported low media exposure, while a large majority used the internet (82.59%). Additionally, 56.28% of participants rated their self-reported health status as good (Table 1).

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Table 1. Descriptive characteristics of reproductive-age women in Lesotho.

https://doi.org/10.1371/journal.pone.0336983.t001

Prevalence of breast cancer screening among reproductive-age women in Lesotho

The prevalence of breast cancer screening among women of reproductive age in Lesotho was 22.20% (95% CI 21.19–23.23) (Fig 1).

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Fig 1. Prevalence of clinical breast cancer screening among reproductive-age women in Lesotho.

https://doi.org/10.1371/journal.pone.0336983.g001

Random effect and model fitness

The model fitness statistics assess the fit of the multilevel logistic regression model to the data. The ICC in the null model was 0.04, indicating that 4% of the variation in breast cancer screening is due to community-level factors (between-cluster variability). The highest PCV value in the final model suggests that most of the variation in breast cancer screening is explained by individual and community-level factors. Model IV had the highest log-likelihood, making it the most suitable model. Additionally, the lowest deviance value in the final model indicates that Model IV is the best explanatory model for the variation in breast cancer screening between clusters (Table 2).

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Table 2. Factors influencing clinical breast cancer screening among reproductive-age women in Lesotho.

https://doi.org/10.1371/journal.pone.0336983.t002

Discussion

This study aimed to assess the prevalence and factors influencing breast cancer screening among women of reproductive age in Lesotho, using Andersen’s healthcare utilization model as a theoretical guide. The model considers predisposing, enabling, and need factors that influence healthcare utilization. The study utilized data from the recent Lesotho Demographic and Health Survey (LDHS) to provide a comprehensive analysis. The findings revealed that the prevalence of breast cancer screening among women of reproductive age in Lesotho was 22.20%. While this figure is higher than in some other sub-Saharan African countries, it still highlights a significant gap in screening coverage. A previous study in Lesotho reported a clinical breast examination (CBE) uptake rate of 9.73% [20]. This lower figure, compared to the current 22.20% prevalence, suggests that although awareness and screening efforts have improved, a substantial portion of the population remains without access to these essential services. Our findings indicated a higher prevalence of clinical breast cancer screening compared to various studies. For instance, a multilevel analysis conducted across six sub-Saharan African countries found an overall prevalence of clinical breast cancer screening was 14.23% [21]. Further studies illustrate varying rates of screening in the region: seven additional sub-Saharan African countries reported a prevalence of 19.2% [37], while specific countries revealed the following figures: Nepal at 6.5% [38], Ghana at 18.39% [39], Kenya at 12% [31], and Tanzania at 6% [40]. Additionally, a multilevel analysis of five sub-Saharan African countries revealed a prevalence of 16.3% [19], while a multi-country analysis of 14 low-resource countries indicated an average screening rate of 15.41% [41]. Interestingly, these figures contrast with the reported prevalence of 22.20% in Lesotho, suggesting that Lesotho exhibits an above-average screening uptake when compared to the overall regional statistics. Another study focusing on breast cancer screening within four sub-Saharan African countries specifically Burkina Faso, Ivory Coast, Kenya, and Namibia found an overall prevalence of 12.9%. Among these countries, Namibia recorded the highest screening rate at 23.1%, while Ivory Coast had the lowest at 5.2% [16]. Thus, the prevalence of 22.20% in Lesotho aligns closely with Namibia’s, indicating that both nations possess relatively higher screening rates within the sub-Saharan context. Additionally, our findings are consistent with those of a systematic review and meta-analysis conducted in low- and middle-income countries, which reported a clinical breast examination screening prevalence of 23.1% [42]. This alignment underscores the potential efficacy of Lesotho’s screening programs and highlights the need for continued efforts to enhance awareness and access to breast cancer screening across the region.

Our study found that the prevalence of clinical breast cancer screening is lower compared to other countries, with Thailand having a screening prevalence of 29% [43], Iran at 60.2% [22], and Vietnam at 51% [44]. These figures suggest that while our findings indicate a lower uptake of breast cancer screening, there are successful models from these countries that might guide future enhancements in screening programs and health education initiatives. The variation in the prevalence of clinical breast cancer screening can be attributed to several factors. In Lesotho, the prevalence is higher than in many sub-Saharan African countries, indicating improved awareness and screening efforts. The use of recent demographic and health survey datasets also highlights these differences. Additionally, disparities in healthcare access, socioeconomic status, and educational levels contribute to the variation in screening rates between countries.

This study applied Andersen’s Behavioral Model to examine the determinants of breast cancer screening utilization, revealing a clear interplay between predisposing, enabling, and need factors [28,45]. In this finding, predisposing characteristics such as age and parity significantly influenced screening behaviour. Older women, particularly those aged 25–34 and 35–49, were more likely to undergo screening compared to their younger counterparts. This finding is consistent with previous studies [16,21,24,26,40], indicating that older women are more aware of the importance of breast cancer screening and are more inclined to participate in such programs. This trend may be due to increased health awareness, more frequent healthcare interactions, and a higher perceived risk of breast cancer among older women. Similarly, our multilevel analysis revealed that being multiparous or grand multiparous women increases breast cancer screening compared to being nulliparous women. This finding aligns with previous studies [19–21,24]. The possible reason for the higher likelihood of breast cancer screening among women with higher parity may be attributed to several factors. Women with higher parity, meaning those who have given birth to multiple children, are more likely to undergo screening due to increased interactions with healthcare providers during pregnancy and childbirth.

Our study findings strongly affirm the role of enabling factors in shaping breast cancer screening behavior, particularly through health insurance coverage, media exposure, and contraceptive use. This study showed that health insurance coverage significantly influences breast cancer screening. Women with health insurance are more likely to undergo screening than their counterparts. This finding aligns with studies [16,19,20,39,40,46], indicating that health insurance increases the likelihood of participating in preventive health services, including breast cancer screening. According to the current study, high media exposure was positively associated with breast cancer screening. Studies have shown that women regularly exposed to health information through media are more likely to participate in screening programs [19–21,24,39,41]. This is because media exposure plays a crucial role in raising awareness about breast cancer and the importance of early detection. The study revealed that contraceptive use is significantly associated with breast cancer screening. This finding aligns with previous studies [19,24,39], showing a positive association between contraceptive use and participation in preventive health services. Women who use contraceptives are more likely to be in regular contact with healthcare providers, increasing their chances of receiving information about breast cancer screening.

According to Andersen’s Behavioral Model, need factors, both perceived and evaluated, are the most immediate determinants of health service utilization [28,45]. In this study, recent visits to healthcare facilities were significantly associated with increased breast cancer screening uptake. This reflects the models assertion that contact with health services often activates perceived health needs and facilitates preventive action. Women who were frequent visitors to healthcare facilities in the past 12 months were positively associated with breast cancer screening. This aligns with other studies [19–21,24,26,39] that emphasize the role of healthcare access in promoting screening. Women who regularly visit these facilities are more likely to receive information about the importance of screening and have improved access to screening services. So, our findings affirm that strengthening routine healthcare access and integrating screening promotion into everyday clinical encounters can significantly improve breast cancer screening rates.

Overall, our findings conclude that Andersen’s model is a strong framework for understanding breast cancer screening behaviour. The patterns we observed highlight a dynamic interplay between individual predisposing factors, enabling factors, and perceived health needs. Future interventions should take these dimensions into account to improve screening coverage, especially among underserved populations.

Strengths and limitations of the study

This study utilizes a large, nationally representative sample from the recent Demographic and Health Survey, enhancing the generalizability of the findings. The application of the Andersen Behavioral Model offers a comprehensive framework for understanding the determinants of breast cancer screening, which is considered a strength of our study. However, there are limitations, including the cross-sectional design that restricts the ability to infer causality. Additionally, the reliance on self-reported data may introduce recall bias and social desirability bias. Further, longitudinal studies are needed to confirm these findings and explore causal relationships.

Conclusion and recommendation

The prevalence of breast cancer screening among women of reproductive age in Lesotho was 22.20%. Significant factors associated with clinical breast cancer screening include age, healthcare facility visits, health insurance coverage, media exposure, contraceptive usage, and parity. These findings highlight the need for targeted interventions to improve screening rates, aligning with the Sustainable Development Goals (SDGs), particularly Goal 3 (Good Health and Well-being). By addressing these factors, we can enhance awareness, access, and affordability of breast cancer screening services. The Anderson Behavioral Model highlights the significance of predisposing, enabling, and need factors in healthcare utilization. Our study confirms that age and parity (predisposing factors), health insurance coverage, contraceptive use, and media exposure (enabling factors), along with healthcare facility visits (need factors), significantly influence breast cancer screening behaviour. By understanding these determinants, policymakers and healthcare providers can develop effective strategies to increase screening rates and ensure equitable access to preventive health services. Policymakers and healthcare providers should focus on increasing access to healthcare, promoting health insurance coverage, leveraging media for awareness campaigns, and encouraging regular healthcare visits to improve breast cancer screening uptake and ultimately reduce mortality rates in Lesotho.

Acknowledgments

We extend our sincere gratitude to MEASURE DHS for granting us access to the Demographic and Health Surveys data.