This study aimed to investigate differences in healthcare access among individuals with OA living in rural and urban areas in Portugal.

The findings indicate that rural residents are 32% less likely (OR 0.68, 95% CI 0.52–0.90) to visit a physiotherapist or related professional compared to their urban counterparts.

Notably, although a higher proportion of rural inhabitants with OA report poor or very poor health status and intense or very intense pain, this does not appear to be directly linked to access to rehabilitation services.

These results align with previous research in Portugal and internationally, which has shown that living in remote geographical areas is associated, on one hand, with higher pain levels (Messier et al., 2024), but, on the other hand, with lower utilization of physiotherapy and other specialized healthcare services among individuals with OA (Costa et al. 2021; Liu et al. 2022).

This pattern underscores the existence of unmet healthcare needs within these populations.

Physiotherapists play a central role in delivering high-value first-line care options for OA management (Briggs et al. 2019), and limited access to physiotherapy treatments may hinder improvements in pain, physical function, and quality of life (Lawford et al. 2024), potentially leading to worse disease progression. Consequently, it is not unexpected that rural individuals exhibit higher rates of total arthroplasty utilization compared to their urban counterparts, as observed in a large cohort of US patients (Hinman et al. 2023).

As outlined earlier, this disparity can be attributed to several factors, where geographical distance from healthcare facilities represents a key factor. Previous data had shown that individuals with OA and living in rural areas consider distance the most common reason for not seeking treatment (Bala et al. 2020). Additionally, rural determinants such as lower education and socioeconomic status (Jiang et al. 2021; Wang et al. 2015), also found in this study, influence health-seeking behaviors (Berkman et al. 2011; Kanungo et al. 2015) and are directly associated with unmet healthcare needs (Chen et al. 2021; McMaughan et al. 2020). Among rural individuals with OA, a previous study found a high proportion of unawareness of the beneficial effects of exercise and physiotherapy for condition management (Bala et al. 2020).

The association between rural residency and a lower likelihood of visiting a rehabilitation professional was more pronounced among younger individuals (≤ 64 years). This disparity may be partially explained by the types of occupational activities typically undertaken in rural versus urban settings. Working-age individuals in rural areas are more likely to be employed in agricultural, manual, or precarious jobs (Matz et al. 2015), which often lack the flexibility or formal provisions—such as paid health leave—required to access healthcare services during working hours. These constraints may hinder their ability to attend physiotherapy or similar appointments. In contrast, individuals working in urban environments are potentially more likely to benefit from structured employment arrangements that facilitate access to health services, and—due to greater proximity and service availability—they typically forfeit less work time when seeking care.

The results of this study also indicate that individuals with OA living in rural areas are 78% more likely (OR 1.78, 95% CI 1.20–2.63) to face difficulties in obtaining medical care due to distance or transportation issues, independently of other determinants. This finding aligns with previously presented data, which highlights geographical distance as a major factor in defining healthcare access. While previous research has established the influence of factors such as age, socioeconomic status, education, and income on healthcare access (Abenoja et al. 2023; Fontaine et al. 2007; Murphy et al. 2017; Reyes and Katz 2021), and the study sample revealed a higher proportion of older participants, with fewer years of education, and lower income in the rural group, the confounder-adjusted OR confirmed a strong association between rural residence and reported waiting times for medical appointments, exams, or treatment due to distance or transportation. This result demonstrates that physical distance to healthcare facilities remains an independent predictor of reduced access, placing rural inhabitants at a disadvantaged and unfair position, and further widening the existing gap in healthcare equity. Previous studies had already highlighted the existence of this “distance decay association” in healthcare, where greater geographical distance from healthcare services is linked to lower utilization and poorer health outcomes (Kelly et al. 2016; Liu et al. 2022).

This association was more prominent in the age group between 65 and 79 years.

A possible explanation is that younger individuals may have greater access to private transportation or better physical mobility to use public transport. In contrast, in older age groups, more pronounced disability or physical dependence, as well as reduced awareness, can impact health-seeking behavior and decrease proactivity in accessing healthcare services.

Regarding the other outcomes considered in the analysis, this study did not find differences in access to hospital outpatient care between rural and urban populations with OA. Outpatient care, which includes services such as consultations and diagnostic tests, often involves a single visit. In contrast, physiotherapy treatments typically require multiple sessions. This could explain the lack of differences observed between the two groups, as rural residents, despite facing access challenges, may be more likely to arrange a one-time visit to a hospital compared to ongoing treatments that necessitate multiple visits.

Concerning waiting times for healthcare access, just over one-third of the sample in each group reported experiencing non-reasonable waiting times for a medical appointment, examination, or treatment in the previous year, with a slightly higher proportion among rural participants. These results reinforce a well-documented challenge in the Portuguese healthcare system, where 47% of individuals waiting for a first hospital specialty consultation are experiencing waiting times that exceed the maximum guaranteed response times (Conselho das Finanças Públicas 2024). This finding underscores that long waiting times for medical care are a widespread problem affecting the Portuguese population, regardless of whether they live in rural or urban areas.

Similarly, a generally high proportion of individuals with OA reported unmet healthcare needs due to financial constraints. Although this study found a higher concentration of individuals in the lowest income quintiles among rural residents—compared to urban residents, who were more frequently in the highest quintile—these income differences were not fully reflected in the reported financial difficulties in accessing care, as both groups appeared to be similarly affected by economic barriers to healthcare. Once again, this finding is not unexpected, as available data indicate that out-of-pocket payments accounted for 29% of total health expenditure in Portugal in 2021, a percentage significantly higher than the OECD average of 18.4%. Additionally, 10.6% of Portuguese households (compared to an EU average of 5.3%) faced healthcare expenses exceeding 40% of their household budget, which is considered a catastrophic spending on health (OECD 2023). Considering the overall impact of healthcare costs on Portuguese families, it is not surprising that no significant differences were found between rural and urban areas, as this seems to be a challenge faced by the entire population.

The results of the current study need to be interpreted in the context of its limitations.

The cross-sectional nature of the data limits the ability to draw causal inferences. Moreover, the reliance on self-reported measures introduces potential sources of bias, such as recall bias and social desirability bias. Previous research has highlighted a general tendency to under-report chronic disease diagnoses, particularly among older adults and individuals with high BMI, which may lead to an underestimation of symptom burden and barriers to accessing care (Liu et al. 2024).

Additionally, the potential presence of residual and unmeasured confounding bias should be considered, as there may be important variables that were not available for adjustment in the analysis, but could have influenced the results. Further research in this area should focus on longitudinal evaluations of healthcare access, examining additional factors such as referral patterns, patient and healthcare professionals’ beliefs and misconceptions, variations in service and transportation availability, and healthcare-seeking behaviors. This would provide deeper insights into the underlying determinants of healthcare access inequalities.

On the other hand, this study presents several strengths. First, the use of a nationally representative survey (INS 2019) ensures robust inferences about the Portuguese population with OA, while the application of survey weights enhances the representativeness of the findings. Additionally, by focusing on healthcare access disparities, the study provides valuable insights into the geographical barriers faced by rural populations, particularly in accessing physiotherapy and other healthcare services. The inclusion of age-group analyses further strengthens the study by revealing age related heterogeneities in healthcare utilization patterns. Importantly, the findings hold significant implications for public health policies, emphasizing the need for alternative strategies—such as digital health solutions—to bridge existing gaps in access.

The findings of this study underscore the urgent need for healthcare services and policies to identify or develop alternative methods of delivering high-value treatments to rural populations with OA. Addressing this challenge requires the implementation of strategies that take into account the specific needs and characteristics of these populations, ensuring they have equal opportunities to achieve the same outcomes as urban inhabitants.

These strategies can vary, such as enhancing community-based care or improving transportation options. However, in the current era, the role of digital health is undeniably being emphasized by various health institutions, and being increasingly recognized as a crucial tool in addressing healthcare disparities (World Health Organization 2021). Significant improvements in clinical and psychosocial outcomes have been widely reported among individuals with chronic musculoskeletal conditions who received various forms of digital interventions. Several systematic reviews have found evidence supporting the effectiveness of digital health interventions in reducing pain intensity, improving functionality and physical performance, enhancing self-management, and promoting better quality of life (Valentijn et al.; Cottrell et al. 2017; Thurnheer et al. 2018; Pfeifer et al. 2020; Chen et al. 2021; Latif-Zade et al. 2021; Xie et al. 2021; Jirasakulsuk et al. 2022; Xiang et al. 2023; Baigi et al. 2023; Thompson et al. 2023).

Furthermore, digital interventions have been found to be cost-effective compared with usual care (Fatoye et al. 2020; Molina-Garcia et al. 2024) and are associated with high levels of satisfaction from both patients and providers (Amin et al. 2022). Although these data are primarily related to urban settings, they provide a promising foundation for extending the benefits of digital health to underserved rural communities. By bridging the gap between urban and rural settings, disparities can be reduced, ensuring that rural populations receive timely and adequate healthcare, regardless of their geographic location.