A Comparative Analysis of Diabetes Self-Care and Treatment Adherence Among Patients with Type 2 Diabetes Mellitus With and Without Cancer

Abstract

Background/Objectives: The co-existence of Type 2 Diabetes Mellitus (T2DM) and cancer presents complex self-management challenges due to competing health demands. This study aimed to evaluate and compare self-care activities and adherence to medical recommendations between T2DM patients with cancer and a non-cancer T2DM control group. Additionally, it investigated the impact of sociodemographic and clinical characteristics on treatment adherence. Methods: A cross-sectional study was conducted in a general hospital in Thessaloniki, Greece, using convenience sampling. The sample consisted of 62 participants: 29 patients with T2DM and cancer and 33 controls with T2DM only. Data were collected using the “Diabetes Self-Care Activities Questionnaire”, analyzing subscales for self-care activities and adherence to medical orders. Results: The cancer group was notably older, with a mean age of 69.8 years compared to 60.3 years in the control group (p < 0.001). While overall adherence scores were comparable between groups, significant disparities existed in specific domains. The cancer group demonstrated a critical neglect of foot care recommendations compared to controls (p < 0.001), with a very large effect size (d = 1.60). Conversely, cancer patients reported significantly stricter adherence to dietary recommendations (p = 0.001, d = 0.96). Within the cancer group, older age and lower education were unexpectedly associated with better foot care adherence (p < 0.05). Conclusions: The results suggest a distinct prioritization among cancer patients, whereby they reported maintaining strict dietary adherence while potentially deprioritizing preventative foot care. Clinical practice should consider transitioning to an integrated model where oncology healthcare professionals actively reinforce diabetic foot surveillance to prevent complications.

1. Introduction

Type 2 Diabetes Mellitus (T2DM) and cancer constitute two of the most significant and rapidly growing public health challenges globally. The prevalence of T2DM has reached epidemic levels, with global prevalence among adults reaching approximately 10.5%, with a potential increase to 12.2% by 2045 [1]. At the same time, cancer remains a leading cause of mortality in the developed world, with nearly 20 million new cases diagnosed annually worldwide [2]. The frequent co-existence of these two pathological entities within the same patient [3] creates a complex and challenging clinical condition that demands special attention from healthcare professionals [4].

T2DM significantly increases the risk of several cancers, including liver, pancreatic, breast, colorectal, and endometrial cancers. Furthermore, the risk increases by 20–50% for colon, breast and bladder cancer. This elevated risk is driven by shared factors such as obesity, as well as biological mechanisms including chronic inflammation, hyperinsulinemia, and hyperglycemia, all of which promote cancer cell growth. However, the strength of this association varies by cancer type, and the influence of diabetes treatments on cancer risk remains under investigation [5].

Both conditions are characterized as chronic diseases requiring long-term monitoring and multifactorial management. The frequent coexistence of T2DM and cancer creates a significant “double burden”, leading to poorer prognosis, increased mortality and treatment-related toxicity, and reduced quality of life. This overlap requires integrated supportive care that addresses treatment-related hyperglycemia (e.g., from corticosteroids), chronic inflammation, nutritional needs, and psychological distress. A multidisciplinary, coordinated care approach is essential to balance cancer treatment with optimal diabetes management, particularly given the bidirectional relationship whereby T2DM increases cancer risk and progression, while some cancer therapies worsen glycemic control [6].

In the context of these chronic diseases, self-care constitutes a cornerstone of therapeutic management [7]. Self-care is the practice of taking responsibility for one’s own health and well-being by being mindful, regulating one’s behaviors, and relying on personal capabilities. It involves cultivating awareness, exercising control over one’s actions, and fostering independence to maintain or improve overall health [8]. In T2DM, self-care is a demanding process that includes, among other things, adopting a healthy diet, engaging in physical exercise, monitoring blood glucose, and performing foot care [9]. On the other hand, self-care in cancer focuses on managing disease symptoms and treatment side effects, as well as psychological and social adjustment [10]. So, when the two diseases co-exist, self-care requirements accumulate, creating a complex living situation for the patient.

A central role in the effectiveness of self-care is played by the concept of adherence to treatment. Adhering to treatment is a crucial health-related behavior for individuals with chronic conditions [11]. According to the World Health Organization, adherence is defined as the extent to which a person’s behavior (e.g., taking medication, following a diet, performing lifestyle changes) corresponds with agreed recommendations from a healthcare provider. It concerns not merely the passive acceptance of medical orders or recommendations, but the active participation of the patient in the management of their health [12].

Achieving high levels of adherence is critical for the outcomes of both diabetes and cancer. Poor adherence is associated with negative outcomes, an increased risk of complications, higher mortality rates [12], more increased healthcare costs [13] and frequent hospitalizations [14]. However, maintaining adherence becomes particularly challenging due to cumulative treatment burden in multimorbidity, as patients struggle to balance the distinct and rigorous guidelines required for each disease simultaneously. Studies show that non adherence is found increased in multimorbidity [15,16,17,18]. In the context of this study, poor adherence is defined as the limited frequency of performing recommended self-care activities. Clinically, this translates into behaviors that deviate from the agreed treatment plan, thereby increasing the risk for acute and chronic complications.

Despite the existing literature regarding adherence in diabetes and cancer separately, there is a considerable research gap regarding the behavior of patients experiencing the co-existence of these two diseases. Few studies have investigated how a cancer diagnosis and its treatment influence specific aspects of diabetic self-care, such as foot care or diet. Understanding these patterns is essential for designing targeted interventions.

Although there are still no official epidemiological data in Greece that record the exact number of patients with both T2DM and cancer, the high incidence of the two diseases separately makes their coexistence an emerging clinical issue. With the prevalence of T2DM in Greece reaching 11.6% [19], and cancer being the second leading cause of death in the country, a significant number of patients are called upon to manage the conflicting demands of these two serious diseases. Given that Greece faces an aging population, a shared risk factor for both malignancy and metabolic disease, the co-existence of these conditions represents a significant strain on the national healthcare system. Understanding local self-care behaviors is therefore critical, as Greek patients may face unique cultural or systemic barriers to treatment adherence compared to those in other developed nations.

Thus, based on the cumulative burden of managing two complex chronic conditions, we hypothesized that patients with co-existing T2DM and cancer would exhibit poorer adherence to preventative self-care tasks, such as foot care, compared to those with T2DM alone, due to the prioritization of acute cancer treatment. Consequently, the primary objective of this study was to compare diabetes self-care activities and adherence to medical recommendations between these two groups. Additionally, a secondary objective was to investigate how sociodemographic and clinical characteristics influence treatment adherence within these distinct populations.

2. Materials and Methods

2.1. Setting and Sample

A cross-sectional study was conducted from March to June 2021. Data collection was carried out at a large central tertiary hospital of Thessaloniki, Greece. As a tertiary hospital, it provides specialized care and serves as a referral center for complex cases. Patients were recruited through convenience sampling from those attending the general medicine outpatient clinic and the diabetes outpatient clinic.

Inclusion criteria for the study groups were: (a) for the clinical group, adults with both T2DM and a cancer diagnosis; (b) for the control group, adults with T2DM and no history of cancer. Common criteria for both groups included knowledge of the Greek language and the desire to voluntarily participate in the research. The total sample consisted of 62 people; 29 with cancer and T2DM, and 33 with T2DM only (response rate 96%). The 96% response rate reflects that while most patients were willing to participate and a small number (N = 3) declined due to time constraints or physical fatigue related to their clinical condition.

While the sample size was determined by convenience sampling during the study period, post hoc analysis indicates that for the primary finding of foot care adherence (effect size d = 1.60), the sample of 62 participants provided sufficient power to detect significant differences between the groups.

2.2. Assessment

The Diabetes Self-Care Activities Questionnaire created and validated in Greek by Intas et al. (2012) was used [20]. It includes 38 items in seven subscales; socio-demographic information; risk factors information (weight, height, body mass index, smoking and duration of diabetes); physical and mental health (combines the Short Form-12 Health Survey and Patient Health Questionnaire-9); physician–patient communication (patients were asked if they see the same physician, and if so, for how many years and how often); self-care activities (adherence and satisfaction with the plans for meals, exercise, foot care and blood glucose control); self-care recommendations (diet, exercise, checking blood glucose and medication); and adherence to medical orders (rating of adherence in diet, medication and foot care on a scale of 0–7 and were asked three questions about smoking) [20].

Specifically, we examined and analyzed the subscales of self-care activities and adherence to medical orders. The completion time was approximately 10 min and Cronbach’s coefficient for the total questionnaire in the present study was 0.821.

The assessment was conducted using printed paper questionnaires to ensure accessibility for all patients, particularly the elderly. Data collection occurred in-person during the patients’ scheduled visits to the outpatient clinics. Researchers approached eligible patients in the waiting area; those who provided written informed consent completed the questionnaire on-site and returned it immediately to the research team. This ‘face-to-face’ paper administration accounts for the high response rate and ensures that data were collected at the point of care rather than relying on patients returning the forms at a subsequent visit.

2.3. Data Analysis

Data analysis was performed using the IBM SPSS^® statistical software package, version 25 (IBM Corp., Armonk, NY, USA). Descriptive statistics were initially calculated to summarize the demographic and clinical characteristics of the sample. Categorical variables are presented as absolute (N) and relative (%) frequencies, while quantitative variables are presented as Mean ± Standard Deviation (SD).

To compare treatment adherence and self-care activities between the two groups (DM with Cancer vs. DM Control), the Independent Samples t-test was utilized. Prior to analysis, the assumption of equality of variances was assessed. In cases where this assumption was violated (Levene’s test), Welch’s t-test was applied to ensure the robustness of the results. For all statistically significant differences observed between the groups, the effect size was calculated using Cohen’s d to determine the clinical magnitude of the difference. Effect sizes were interpreted according to standard criteria: values of 0.20, 0.50, and 0.80 were considered small, medium, and large effects, respectively.

Adherence to foot care recommendations was defined as the primary outcome of the study, given its clinical significance in preventing diabetes-related complications. All other subscale analyses, including dietary adherence and sociodemographic subgroup comparisons, were considered exploratory in nature. This hierarchical approach was adopted to minimize the risk of Type I errors (false-positive findings) inherent in multiple unadjusted comparisons within a small sample size.

For the subgroup analyses, certain demographic variables were dichotomized (e.g., age ≤ 69 vs. >70 years; primary/secondary vs. higher education). This approach was utilized to ensure sufficient group sizes for statistical comparison via t-tests and to facilitate the interpretation of self-care patterns within the specific clinical context of this small sample.

Furthermore, additional subgroup analyses were conducted to investigate the impact of demographic and clinical characteristics (e.g., age, education, BMI, radiotherapy) on adherence scores within each group separately. These comparisons were also performed using Student’s t-test. Associations between categorical demographic variables were assessed using Pearson’s Chi-square (chi2) test where applicable. All statistical tests were two-tailed, and the significance level was set at p < 0.05.

2.4. Ethics

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics and Deontology Committee of the International Hellenic University, Thessaloniki, Greece (7th/17-3-2021). Written informed consent was obtained from all participants prior to their inclusion in the study. Participants were assured of anonymity and confidentiality of their responses.

3. Results

3.1. Demographic and Clinical Characteristics

We compared 29 patients with DM and cancer against a control group of 33 patients with DM only (Table 1). The cancer group was notably older, with a mean age of 69.8 years compared to 60.3 years in the control group (p < 0.001). There was a significant disparity in education levels. While the majority of the control group (63.6%) possessed higher education degrees, the vast majority of the cancer group (89.7%) had completed only primary or secondary education (p < 0.001).

Table 1. Demographic and clinical characteristics of patients.

Variable	Category	DM and Cancer (N = 29)	DM Control (N = 33)	p-Value
Demographics		N (%)	N (%)
Gender	Male	17 (58.6%)	20 (60.6%)	0.87
	Female	12 (41.4%)	13 (39.4%)
Age (years)	Mean ± SD	69.79 ± 7.74	60.33 ± 9.97	<0.001
Marital Status	Married	23 (79.3%)	25 (78.1%)	0.91
	Other (Single/Widowed/Divorced)	6 (20.7%)	7 (21.9%)
Education Level	Primary/Secondary	26 (89.7%)	12 (36.4%)	<0.001
	Higher/University	3 (10.3%)	21 (63.6%)
Anthropometrics
BMI	Normal (<25)	4 (15.4%)	13 (39.4%)	0.06
	Overweight/Obese (>25)	22 (84.6%)	20 (60.6%)
Habits	Smoking (Yes)	6 (20.7%)	9 (27.3%)	0.54
	Alcohol Consumption (Yes)	3 (11.1%)	6 (18.2%)	0.44
Diabetes (DM)
DM Duration (years)	Mean ± SD	9.64 ± 9.45	10.94 ± 8.07	0.55
DM Treatment	Oral agents only	17 (58.6%)	23 (69.7%)	0.36
	Insulin (+/− Oral agents)	12 (41.4%)	10 (30.3%)
DM Complications	Cardiovascular *	5 (17.9%)	5 (15.2%)	0.77
	Microvascular **	7 (24.9%)	3 (9.1%)	0.12 †
	Other Complications	4 (14.3%)	1 (3.0%)	0.16 †
Cancer Data
Cancer Duration (years)	Mean ± SD	5.30 ± 6.07
Tumor Site	Colorectal	6 (21.4%)
	Breast	5 (17.9%)
	Lung	4 (14.3%)
	Prostate	4 (14.3%)
	Other types	9 (32.0%)
Stage	Stage IV	11(38.0%)
	Stage II–III	9 (31.0%)
	Stage I	9 (31.0%)
Metastasis	Yes	20 (69.0%)
	No	9 (31.0%)
Treatment	Surgery	16 (66.7%)
	Radiotherapy	10 (41.7%)
	Targeted/Hormonal	6 (25.0%)

Values calculated using Pearson’s Chi-square test for categorical variables and t-test for continuous variables; SD: Standard Deviation; * Cardiovascular: Coronary artery disease, acute myocardial infarction, aortic οr carotid stent; ** Microvascular: Neuropathy, retinopathy, nephropathy; † Despite the percentage difference, these specific complications did not reach statistical significance (p < 0.05) due to the small sample size in these sub-categories (e.g., only 3 control patients had microvascular issues).

Although the duration of diabetes was similar between the two groups (approximately 10 years), the cancer group appeared to have more difficult-to-manage diabetes. This is evidenced by a higher rate of insulin use (41.4% vs. 30.3%) and a significantly higher prevalence of microvascular complications (24.9% vs. 9.1%) compared to the control group, although this did not reach statistical significance (p = 0.12).

Among the cancer patients, the disease was mostly advanced (38% were at Stage IV), and 69% had metastases. The most common malignancies were colorectal cancer (21.4%) and breast cancer (17.9%). The primary treatment modality was surgery (66.7%), followed by radiotherapy (41.7%).

It is important to note that no patients in either the cancer or control group had already recognized or active diabetic foot ulcers at the time of the study. The focus of the assessment was on preventative foot care behaviors rather than the management of existing wounds.

3.2. Descriptive Data of the Questionnaire’s Subscales and Comparisons Between Groups

Regarding the Self-Care Activities subscale (Table 2), the control group generally demonstrated slightly better engagement in self-care activities compared to the cancer group (Overall Score: 3.76 vs. 3.37). The most notable difference was observed in Foot Care, where the control group scored significantly higher (4.06) compared to the cancer group (2.20). Conversely, the cancer group appeared to follow a Special Diet slightly more strictly than the controls (4.34 vs. 3.82). There was no statistically significant difference in the overall Self-Care Activities score between the DM Control group and the DM and Cancer group (p = 0.22). However, a significant difference was found in Foot Care activities (p = 0.04).

Table 2. Adherence to DM treatment by group.

Variable	DM Control (N = 33)	DM and Cancer (N = 29)	t (df) *	p-Value
Self-Care Activities (Overall)	3.76 ± 1.34	3.37 ± 1.13	1.25 (60)	0.22
General Diet	4.41 ± 1.74	4.46 ± 2.19	−0.11 (59)	0.91
Special Diet	3.82 ± 1.16	4.34 ± 1.43	1.57 (59)	0.12
Exercise	1.39 ± 1.30	1.07 ± 1.41	0.93 (59)	0.36
Blood Glucose Control	5.14 ± 2.08	4.76 ± 2.56	0.64 (60)	0.52
Foot Care	4.06 ± 2.89	2.20 ± 1.98	2.89 (56.70)	0.04
Adherence to Medical Orders (Overall)	4.58 ± 0.54	4.52 ± 0.87	0.30 (45.88)	0.76
Diet Recommendations	0.23 ± 0.88	1.73 ± 1.99	−3.79 (33.19)	0.001
Exercise Recommendations	7.00 ± 0.00	7.00 ± 0.00	—	1.00 †
Foot Care Recommendations	6.30 ± 0.96	4.42 ± 1.36	6.29 (59)	<0.001

Results are presented as Mean ± Standard Deviation (SD); * Welch’s t-test used due to unequal variances; † Both groups had identical means and zero standard deviation. Therefore, the difference is strictly zero.

Then, as far as it concerns the Adherence to Medical Orders subscale (Table 2), overall adherence levels were similar between the two groups (4.52 vs. 4.58), showing no significant difference (p = 0.76). Both groups reported identical maximum scores for adherence to exercise recommendations resulting in zero variance. This outcome rendered a formal statistical comparison between the groups uninformative for this specific variable and suggests a significant ceiling effect within the adherence subscale for the study population.

In the diet recommendations, the DM and Cancer group had a higher score compared to the DM Control group, a difference that was statistically significant (p = 0.001). However, a major discrepancy was again found in Foot Care adherence. The control group reported high adherence (6.30), whereas the cancer group reported significantly lower adherence (4.42), with a statistical significance of p < 0.001, confirming the finding from the self-care subscale.

Then, an analysis of effect sizes (Cohen’s d) was conducted to determine the clinical importance and strength of these differences (Table 3). The analysis revealed a very large effect size (d = 1.60) regarding adherence to foot care recommendations, indicating a substantial disparity between the two groups. Similarly, the difference in adherence to diet recommendations showed a large effect size (d = 0.96), with cancer patients perceiving significantly stricter adherence. Finally, the difference in actual foot care activities represented a medium-to-large effect (d = 0.75), suggesting that the statistical significance observed is backed by a meaningful difference in daily patient behavior.

Table 3. Analysis of effect sizes for statistically significant differences between groups.

Variable	Group with Higher Score	Mean Difference	p-Value	Cohen’s d	Effect Magnitude
Foot Care (Self-Care Activity)	DM Control	1.86	0.04	0.75	Medium to Large
Diet Recommendations (Medical Adherence)	DM and Cancer	1.50	0.001	0.96	Large
Foot Care Recommendations (Medical Adherence)	DM Control	1.88	<0.001	1.60	Very Large

3.3. Effects of Demographic Characteristics on Adherence per Diabetes Group

Table 4 presents only the statistically significant relationships between the subscales and the demographics of patients with DM and cancer. Older patients (>70 years) performed significantly better in Foot Care compared to younger patients (p = 0.04). Patients with lower education levels (primary/secondary) reported significantly higher adherence to Foot Care compared to those with higher education (p = 0.02). Patients undergoing radiotherapy showed significantly higher adherence to Diet Recommendations compared to those who did not receive radiotherapy (p = 0.02). In the DM and cancer group, no statistically significant relationships were observed between the subscales and age, duration of DM, treatment for DM, duration of cancer and stage of cancer (p > 0.05).

Table 4. Statistically significant relationships between the subscales and the demographics of patients with DM and cancer (N = 29).

Dependent Variable	Factor (Comparison)	Group 1	Group 2	t (df)	p-Value
Foot Care (Self-Care Activity)	Age	≤69 years 1.43 ± 1.52	>70 years 2.96 ± 2.14	−2.19 (26)	0.04
Foot Care (Self-Care Activity)	Education	Primary/Middle School 3.17 ± 2.25	High School/University 1.47 ± 1.43	2.44 (26)	0.02
Diet Recommendations (Medical Adherence)	Radiotherapy	No 1.00 ± 1.59	Yes 2.90 ± 2.08	−2.63 (24)	0.02

Results are presented as Mean ± Standard Deviation (SD); p-values were calculated using Student’s t-test for independent samples to compare means between subgroups; DM: Type 2 Diabetes Mellitus; df: degrees of freedom.

Following this, Table 5 presents only the statistically significant relationships between the subscales and the demographics of patients with DM. Patients with higher education showed significantly better adherence to foot care recommendations compared to those with primary/secondary education (p = 0.03). Also, patients with DM and a BMI < 25 (Normal weight) followed their special diet significantly better compared to overweight/obese patients (BMI > 25), who scored lower (p = 0.03). In the DM group, no statistically significant relationship was observed between the subscales and gender, age, duration of DM, treatment for DM (p > 0.05).

Table 5. Statistically significant relationships between the subscales and the demographics of patients with DM (N = 33).

Variable	Factor	Group 1	Group 2	t (df)	p-Value
Foot Care Recommendations (Adherence)	Education	Primary–Secondary 5.83 ± 1.11	Higher Education 6.58 ± 0.75	−2.92 (30)	0.03
Special Diet (Self-Care Activity)	BMI	BMI < 25 4.35 ± 1.05	BMI > 25 3.48 ± 1.12	2.24 (31)	0.03

Results are presented as Mean ± Standard Deviation (SD); Comparisons between groups were performed using Student’s t-test; DM: Type 2 Diabetes Mellitus; BMI: Body Mass Index; df: degrees of freedom.

4. Discussion

The primary aim of this study was to compare diabetes self-care activities and adherence between patients with T2DM co-existing with cancer and a control group of T2DM patients. The study observed that while overall self-care and adherence scores were similar between the two groups, significant disparities exist in specific sub-domains. The most profound finding was the substantial neglect of foot care among cancer patients compared to controls, evidenced by a very large effect size (d = 1.60) regarding adherence to medical recommendations. Conversely, patients with cancer reported significantly stricter adherence to dietary recommendations.

Cancer patients with DM scored significantly lower in foot care as a self-care act and as adherence treatment recommendations. The difference in actual foot care activity showed a medium-to-large effect (d = 0.75), while the difference in following recommendations showed a very large effect (d = 1.60). Adherence is often compromised when patients must navigate the complex protocols of multiple chronic conditions, leading to a process of therapeutic prioritization where acute concerns take precedence over preventative measures [14].

These findings suggest that cancer patients may knowingly disregard foot care advice, potentially due to physical limitations, fatigue, or psychological distress associated with their cancer treatment. This is in line with the scoping review of Budhwani et al. (2019) [10], who noted that self-management in advanced cancer is primarily driven by the urgent need to control symptoms and maintain daily functioning. In this context, asymptomatic, preventative tasks like diabetic foot checks are likely viewed as less critical and are thus deprioritized by patients struggling with the high symptom burden of advanced malignancy.

Moreover, they align with findings from a systematic review by Pettit et al. (2017) which concluded that glycemic control often worsens during cancer treatment precisely because patients and clinicians prioritize cancer survival over diabetes self-management tasks [21]. Although 38% of our sample presented with Stage IV disease, no statistically significant relationship was observed between cancer stage and self-care subscales (p > 0.05). Consequently, we cannot definitively conclude that disease stage is a primary driver of adherence patterns based on the current data.

A crucial physiological factor likely contributing to this neglect is the cumulative impact of Chemotherapy-Induced Peripheral Neuropathy (CIPN) exacerbating the underlying diabetic neuropathy. Many of our patients with advanced cancer were likely exposed to neurotoxic chemotherapy agents (e.g., platinum compounds, taxanes), which are known to cause sensory loss in a ‘stocking-glove’ distribution [22]. Research indicates that diabetic patients are at a significantly higher risk of developing severe CIPN due to pre-existing nerve damage, creating a ‘double-hit’ phenomenon [23,24]. Paradoxically, this profound loss of sensation may lead to behavioral neglect; because patients do not feel pain, friction, or minor injuries, they may falsely perceive their feet as ‘healthy’ and thus skip daily feet inspections. As noted by Dars et al. (2025) despite this heightened risk for ulceration, podiatry services remain vastly underutilized in cancer care, leaving these high-risk patients unmonitored [25].

Interestingly, the cancer group exhibited significantly stricter adherence to dietary recommendations (p = 0.001, d = 0.96), a finding consistent with the ‘teachable moment’ hypothesis where cancer prompts the adoption of health-promoting behaviors [26]. This creates a distinct dichotomy; patients adhere to diet but neglect foot care. This pattern is likely attributable to the directive role of the oncology team, since patients are highly responsive to provider-endorsed changes [27]. The deficit in foot care suggests that while diet is frequently reinforced in oncology settings, diabetic foot management remains an overlooked area of clinical guidance.

Furthermore, our subgroup analysis revealed that patients undergoing radiotherapy showed significantly higher adherence to diet recommendations (p = 0.02). This could be attributed to the structured nature of radiotherapy, which often involves frequent contact with healthcare providers and specific nutritional counseling and education to manage radiation side effects, thereby inadvertently improving diabetes dietary compliance [28,29].

Both groups reported identical scores for adherence to exercise recommendations. In a systematic review, physical exercise was the self-care activity that was performed less frequently by individuals with T2DM and adherence to medication was the most frequent behavior [9]. Then, in another review on advanced cancer patients, adherence with physical exercise was reported in about 70% [30].

It is important to note that the cancer group exhibited clinical heterogeneity regarding the type of malignancy (including colorectal, breast, and lung cancer) and disease stage. While the majority had Stage IV disease, the varying physical burdens and treatment regimens associated with different cancer types may impact self-care capabilities in ways that a pooled analysis could not fully differentiate. For instance, patients with colorectal cancer often receive nutritional counseling to manage bowel symptoms, which naturally overlaps with diabetes dietary guidelines and may have contributed to the superior dietary adherence observed in our study. Conversely, patients with advanced breast or lung cancer receiving neurotoxic chemotherapy (e.g., taxanes, platinums) face a disproportionate risk of peripheral neuropathy, which might explain the specific neglect of foot care due to sensory loss rather than simple non-adherence.

The influence of demographic factors in our study was unexpected. While significant baseline disparities in age and education existed between the groups, these factors do not fully explain the observed results. Contrary to general literature trends where higher education usually predicts better adherence to treatment [31,32], our study found that patients with DM and cancer with lower education and older age (>70 years) performed significantly better in foot care. This unexpected result might suggest that older, less educated patients may rely more heavily on caregivers or family members who assist with these daily tasks [33], whereas younger patients may have competing life demands, lack such support or be overwhelmed by managing dual conditions independently [34]. In addition, in the control group, the results indicated that higher education was associated with better foot care adherence (p = 0.03), and normal BMI was associated with better adherence to special diets (p = 0.03). This stands with recent findings by Amerzadeh et al. (2024), who reported generally suboptimal self-care behaviors among elderly diabetic patients, particularly those with lower education levels [35]. Overall, the presence of cancer may override traditional demographic predictors of self-care. These self-care deficits were likely driven by the cancer burden and prioritization of anticancer therapies, which seem to override the influence of baseline demographic characteristics. Nevertheless, although these subgroup associations reached statistical significance, we acknowledge that the small number of participants in these stratified categories limits their statistical power.

Regarding gender, our study did not observe statistically significant differences in self-care behaviors between male and female participants. This stands in contrast to the systematic review by Baroni et al. (2022), which highlighted distinct gender related patterns, such as men performing better in physical activity and women in daily monitoring [36]. The absence of such differences in our sample possibly implies that the burden of cancer may act as a homogenizing factor, diminishing traditional gender-based variations in self-care prioritization.

The results of this study have immediate practical applications. While we observed a higher descriptive percentage of microvascular complications in the cancer group (24.9% vs. 9.1%), this difference was not statistically significant (p = 0.12), likely due to the limited sample size. Therefore, while these descriptive figures are noteworthy, they must be interpreted with caution as the study may be underpowered to confirm this specific clinical disparity. Nevertheless, it is possible that cancer patients are more vulnerable for diabetic foot ulcers. This vulnerability is further underscored by recent evidence in colorectal cancer patients (who constituted a significant percentage of our sample) indicating that the co-existence of T2DM has a negative impact on morbidity and survival [37]. Oncology healthcare professionals should not assume that diabetic self-care is being maintained. Instead, foot examinations should be integrated into routine oncology follow-ups, particularly for younger patients with DM and cancer who, according to our data, are less likely to perform these checks than older patients.

The necessity for such an integrated approach is strongly supported by qualitative evidence. A study on patient perspectives revealed that individuals with co-existing diabetes and cancer often feel overwhelmed by the complexity of dual management and report a significant lack of guidance on how to balance these competing health demands. Participants specifically expressed a need for ‘designated providers’ to bridge the gap between oncology and diabetes care [38]. This mirrors our own findings, suggesting that the neglect of foot care in our sample may not stem from patient indifference, but from a systemic failure to provide clear, prioritized support for diabetes self-management within the oncology setting.

Nevertheless, the interpretation of our findings is constrained by several limitations. First, the use of a cross-sectional approach precludes the establishment of causal relationships; while we identified significant associations between cancer status and specific self-care behaviors, we cannot determine if these behaviors changed specifically as a result of the cancer diagnosis or existed prior to it. This constraint is compounded by the use of convenience sampling at a single medical center with a relatively small sample size (N = 62), which was further reduced during subgroup analyses, and limits the generalizability of our results to the broader population of diabetic patients with cancer. As a result, the study may have been underpowered to detect smaller effects, and certain non-significant findings (null results) should be interpreted with caution as they may represent Type II errors. Furthermore, the unexpected associations found in subgroup analyses—such as the relationship between lower education and better foot care—while statistically significant, may be less reliable due to the limited number of participants in those specific categories. These findings should therefore be considered hypothesis-generating rather than definitive. Also, the small sample size precluded the use of multivariable regression analysis, which would have been ideal to isolate the independent effects of cancer status from confounding variables like age and education.

Moreover, certain relevant clinical biomarkers, such as HbA1c levels, were not evaluated at the time of data collection. The absence of objective glycemic control data may further limit the interpretation of the results, as self-reported adherence could not be cross-referenced with biochemical outcomes. In addition, a pronounced ceiling effect was observed in the Adherence to Medical Orders subscale regarding exercise, where all participants reported maximum scores. This lack of variance indicates that the measurement instrument may lack the sensitivity required to differentiate exercise behaviors in this specific population, representing a valid limitation in the interpretation of these particular results.

Furthermore, the non-randomization of the sample resulted in significant baseline disparities between the two groups. The cancer group was significantly older (p < 0.001) and possessed lower education levels (p < 0.001) compared to the control group. Although subgroup analyses were conducted to account for these factors, the groups were not matched, introducing potential confounding variables that may have influenced the adherence scores. Possibly, the observed neglect of foot care in the cancer group is likely driven by the clinical burden of the malignancy and its treatment rather than demographic factors alone. Nonetheless, future studies with larger, matched cohorts are necessary to confirm these patterns through multivariable modeling. Finally, the reliance on self-reported questionnaires is susceptible to the subjectivity of the assessments as patients may overestimate their adherence or underreport negative health behaviors.

5. Conclusions

This study highlights the complex and often competing demands faced by patients managing both Type 2 DM and a co-existing cancer. The observations in this study point toward a distinct dichotomy in self-care behaviors. While cancer patients demonstrate resilience through strict adherence to dietary recommendations, they exhibit a critical and statistically significant neglect of foot care compared to non-cancer controls. This disparity provides preliminary evidence that the burden of cancer treatment might displace preventative diabetes tasks, placing these patients at heightened risk for complications despite their adherence in other areas.

Therefore clinical practice necessitates a paradigm shift away from isolated care strategies to an integrated model where oncology healthcare professionals actively reinforce diabetes self-management, with a specific emphasis on foot surveillance. Future research should prioritize longitudinal, multicenter studies with larger sample sizes to validate these patterns and establish causal links. Additionally, qualitative inquiries into the patient experience would be valuable to uncover the specific psychosocial barriers hindering self-care, ultimately guiding the development of targeted educational interventions that support the unique vulnerabilities of this dual-diagnosis population.