Cancer is a major global public health concern, ranking as the second leading cause of death worldwide. In 2020, an estimated 19.3 million new cancer cases and nearly 10 million cancer-related deaths were reported, with projections indicating a rise to 28.4 million cases annually by 2040 (1). The most commonly diagnosed cancers include breast, lung, colorectal, prostate, and stomach cancer, with significant variations across regions and populations (2). Low- and middle-income countries (LMICs) bear a disproportionate burden, with limited healthcare access and late-stage diagnoses contributing to high mortality rates (3). In India, cancer incidence is also on the rise, with approximately 1.39 million new cases and nearly 850,000 deaths in 2020 (4). The most prevalent cancers in the country include breast, oral, cervical, lung, and stomach cancers, which account for a substantial portion of the disease burden (5). Regional disparities, healthcare accessibility issues, and financial constraints contribute to delayed diagnosis and suboptimal treatment, leading to poor survival outcomes (6).

The increasing burden of cancer emphasize the importance of addressing disparities in healthcare access, treatment adherence, and patient outcomes. Social determinants of health (SDH) play a crucial role in shaping cancer risk, progression, and survival by influencing socioeconomic status, healthcare accessibility, lifestyle behaviors, social support, and psychological well-being (7). Socioeconomic inequalities often lead to delayed diagnoses and limited treatment options, particularly among disadvantaged populations (8). Geographic barriers, lack of health insurance, and financial constraints further hinder access to timely and appropriate care (9). Additionally, factors such as tobacco use, alcohol consumption, poor diet, and sedentary lifestyles contribute significantly to the rising cancer burden (10). The psychological impact of cancer, including stress, anxiety, and depression, also affects treatment adherence and quality of life (11). Understanding the influence of these determinants is essential for developing effective interventions aimed at reducing disparities and improving cancer care.

Despite increasing recognition of SDH in cancer care, there remains a gap in comprehensive research assessing multiple SDH factors simultaneously, particularly in the Indian context. Most studies focus on isolated determinants such as income or healthcare access, without considering the interconnected nature of these factors and their cumulative impact on patient outcomes (12). This study aims to determine prevalence of non-medical (social) needs and identify the factors associated with at least one such need among adult cancer patients attending a tertiary care center in Kochi, Kerala, India.

As shown in Table 1, most patients were aged 60–69 years (n = 113; 31.2%), female (n = 233; 64.4%), and Hindu (n = 268; 74.0%). Half were unemployed (n = 184; 50.83%), and the majority had tertiary education (n = 230; 63.5%). Most held an Above Poverty Line (APL) ration card (n = 318; 87.9%), belonged to nuclear families (n = 272; 75.1%), were married (n = 298; 82.3%), and resided in urban areas (n = 189; 52.2%). Chronic illness was reported by 158 (43.7%), and family history of cancer by 101 (28.1%). The most common stage at diagnosis was stage 3 (n = 137; 38.0%), and the majority were advised chemotherapy (n = 318; 87.9%).

As presented in Table 2, the most frequently reported needs were employment or regular income (n = 145; 40.1%), transportation (n = 83; 22.9%), and payment of utility bills (n = 74; 20.4%). Overall, 220 patients (60.8%, 95% CI 55.5%−65.8%) reported at least one non-medical need, while 142 (39.2%) reported none (Figure 1).

Sociodemographic and clinical factors associated with any non-medical need are presented in Table 3. Patients aged < 50 years (APR 1.37; 95% CI: 1.01–1.84; p = 0.042) and 51–59 years (APR 1.42; 95% CI: 1.09–1.85; p = 0.008), those with primary education (APR 1.50; 95% CI: 1.20–1.86; p < 0.001) or secondary education (APR 1.28; 95% CI: 1.04–1.57; p = 0.020), and patients from BPL households (APR 1.24; 95% CI: 1.02–1.50; p = 0.028) were significantly more likely to report at least one non-medical need.

This cross-sectional study revealed that 60.8% of adult cancer patients in Kerala reported at least one non-medical or social need, underscoring the role of social determinants of health in influencing cancer outcomes. The most frequently cited needs employment (40.1%), transportation (22.9%), and to pay utility bills (20.4%) reflect the multidimensional financial and logistical strain associated with cancer care. These findings align with the work of Zafar et al. (8), who described “financial toxicity” among insured cancer patients in the United States, demonstrating that out-of-pocket expenses and work loss contribute substantially to distress. Similarly, Mallath et al. (6) observed that up to 60.0% of Indian patients experience catastrophic health expenditures during treatment. Hence, despite Kerala's relatively advanced healthcare system, economic pressures continue to act as barriers to equitable cancer care access.

Our prevalence of 60.8% for any non-medical need aligns with recent Indian evidence showing widespread unmet supportive care requirements. Gupta et al. (14) reported that all 256 cancer patients in rural North India had palliative care needs spanning biopsychosocial domains, while 56.6% had moderate-to-severe physical and social symptoms such as pain, transportation barriers, and social discrimination. Likewise, Muralidharan et al. (15) found that 89% of caregivers in Pune reported financial stress, emotional exhaustion, and time burden, especially among spouses balancing employment with caregiving. These parallels reinforce that social hardship persists across settings, irrespective of regional development indicators, signifying structural weaknesses in cancer care systems. Qualitative research supports our findings that unmet needs often extend beyond financial aspects to include communication and psychosocial domains. Chawak et al. (16) reported that Indian cancer patients frequently experienced unsatisfactory communication with healthcare providers and inadequate emotional support from peers, leading to unmet expectations from their support networks. This aligns with our patients' high prevalence of socioemotional challenges. Together, these studies underscore that comprehensive cancer care in India requires greater attention to psychosocial and informational dimensions, not merely medical treatment.

Globally, disparities in supportive care needs reflect systemic inequities. Williams et al. (17) explained that social determinants such as neighborhood environment, education, and healthcare access: create reinforcing cycles that sustain global cancer disparities. Chan et al. (18) in a multinational survey of supportive care specialists, found that LMIC respondents prioritized issues like transportation, drug affordability, and guideline implementation; mirroring the main barriers identified in our cohort. Conversely, in high-income countries (HICs) like Australia, Molassiotis et al. (19) demonstrated markedly lower unmet psychosocial needs, attributable to integrated welfare systems and coordinated oncology services. Thus, our findings reflect a persistent divide between HICs and LMICs in meeting cancer patients' non-medical needs.

Despite such contrasts, even HICs face challenges in integrating psychosocial care. Signorelli et al. (20) reported that while 39% of centers in HICs routinely performed distress screening, only 25% globally offered structured psychosocial interventions, citing barriers like limited workforce and insufficient policy support. These global insights contextualize our findings within a broader continuum of care inadequacies and highlight that equity in oncology extends beyond clinical advancements to encompass systemic social protection mechanisms.

In this study younger patients exhibited a significantly higher prevalence of unmet non-medical needs. Patients aged below 50 years and those between 51–59 years were more likely to report at least one such need. This trend highlights that working-age patients face the dual burden of illness and financial disruption due to employment loss or reduced productivity. Comparable findings have been reported by Haier et al. (9), who emphasized that productivity loss during cancer treatment contributes to downward economic mobility and unmet supportive care needs, particularly in LMICs. Moreover, the National Cancer Registry Programme reported a rising trend of cancer in younger adults (4), further amplifying the urgency to address these economic challenges during active disease management.

In our study, educational attainment was another key determinant, with patients having primary education and secondary education demonstrating greater unmet needs compared to those with tertiary education. This observation aligns with the WHO framework on social determinants of health, which underscores the role of education in empowering patients to navigate healthcare systems effectively (7). Similar patterns have been described by Islami et al. (10), who found that low educational levels were associated with poorer health literacy and increased delays in treatment initiation. In our setting, limited education may hinder awareness of financial aid programs, insurance benefits, or rehabilitation services, compounding the likelihood of unmet social needs. Targeted health education and literacy-sensitive interventions are therefore essential to mitigate these inequalities.

Economic status also played a substantial role, as patients BPL households in this study had higher likelihood of reporting at least one non-medical need. The proportion of participants belonging to BPL households in our study was considerably lower than that reported in the general population of Kerala, suggesting a possible underrepresentation of economically disadvantaged groups. This lower representation is likely because the study was conducted in a private tertiary cancer care center, where poorer patients are less likely to seek treatment compared to public sector hospitals. This observation is further supported by the Economic Review 2024 of the Government of Kerala, which reports a substantially higher proportion of BPL households in the state than that observed in our study (21), underscoring the socioeconomic selectivity of patients accessing private cancer care. The economic gradient observed here is consistent with evidence from the National Cancer Registry, which indicates that out-of-pocket payments account for up to 70% of cancer-related expenditures in India (4). Similarly, Zafar et al. (8) and Islami et al. (10) observed that lower-income groups, even in high-income countries, face greater levels of treatment-related financial hardship. Our data reaffirm that poverty not only influences access to care but also sustains long-term psychosocial and material vulnerabilities throughout the cancer care continuum. Expanding financial protection schemes and improving BPL eligibility for cancer-specific assistance could significantly alleviate such disparities. The findings from our study suggest the urgent need to institutionalize screening for social determinants of health within oncology practice. The WellRx tool, used in this study, has previously demonstrated feasibility for identifying and addressing social needs within primary care settings (13). Integrating such screening into oncology clinics could guide targeted interventions: financial counseling, travel subsidies, and social welfare linkage programs: particularly for vulnerable groups such as younger, low-educated, and BPL patients.

The study's strengths include the use of a validated WellRx tool, ensuring reliable and generalizable findings. However, as the study was conducted in a single private tertiary hospital in urban Kochi, the findings may not reflect the situation in public hospitals or rural areas, where unmet needs could be higher due to greater socioeconomic constraints. In addition, data collection was limited to a short, fixed period (August–September 2025), which may have introduced selection bias, as patients presenting during this timeframe may not fully represent the broader cancer patient population across different seasons or periods. The reliance on self-reported data may have introduced social desirability bias, as patients could underreport sensitive issues such as financial distress or family problems; although interviewer training helped minimize this, it cannot be fully eliminated. Patients with advanced-stage disease or hospitalization were excluded to ensure uniform data collection, possibly leading to an underestimation of true unmet needs in the sickest populations. Finally, given the cross-sectional design, causal relationships between sociodemographic factors and unmet needs cannot be inferred.

More than half of the patients reported unmet needs, with economic, educational, and age-related disparities strongly influencing vulnerability. Targeted support is particularly warranted for patients who are unemployed, have lower educational attainment, belong to BPL households, or are aged 51–59 years. Systematic screening and targeted social interventions are essential to achieve equitable, patient-centered oncology outcomes in India and similar resource-limited contexts. Expanding public-sector coverage and developing low-cost, community-based psychosocial support models can help close the disparity gap between LMICs and HICs.