The Burden of Stigma in Type 2 Diabetes: Evidence from a Rural Primary Care Sample in Türkiye

Abstract

Objectives

This study aimed to evaluate the presence of diabetes-related stigma and its relationship with disease control and family functioning among adults with type 2 diabetes mellitus (T2DM) living in rural Türkiye. A cross-sectional study was conducted between March and May 2025 at a Family Health Center (FHC). A total of 201 adults with physician-diagnosed T2DM participated in the study.

Methods

Data were collected through face-to-face interviews using a sociodemographic questionnaire, the Diabetes Stigma Assessment Scale-2 (DSAS-2), and the Family APGAR scale, which assesses family functioning. Statistical analyses included correlation tests, group comparisons, and logistic regression to identify independent predictors of stigma.

Results

The mean total DSAS-2 score was 39.4±9.2, indicating a moderate level of perceived stigma. Higher stigma scores were associated with very low income, polypharmacy, and the presence of comorbid chronic diseases (p<0.05). A positive correlation was found between the number of children and both the “Treated Differently” and “Self-Stigma” subdimensions of the DSAS-2 (r=0.202 and r=0.216, respectively). Family APGAR scores were generally high (mean=8.9±2.0), but no significant association was observed between family functioning and stigma levels. Logistic regression analysis showed that medication use was independently associated with higher stigma (OR: 2.48; 95% CI: 1.23–4.98; p=0.011), whereas moderate income was associated with lower stigma (OR: 0.165; 95% CI: 0.048–0.567; p=0.004).

Conclusion

Diabetes-related stigma remains a notable psychosocial challenge for adults with T2DM in rural settings. Socioeconomic disadvantage, comorbidity, and family burden contribute to the internalization of stigma, whereas family support alone may not mitigate its effects. Addressing stigma within primary care through culturally tailored psychoeducation and empowerment programs may enhance both emotional well-being and disease management in rural populations.

Diabetes mellitus is among the most prevalent chronic diseases worldwide, imposing profound physical, psychological, and social burdens on affected individuals. According to the International Diabetes Federation (IDF) Diabetes Atlas 2025, approximately 589 million adults are currently living with diabetes, a figure expected to exceed 850 million by 2050.^[1] This escalating prevalence highlights the urgent need to address not only the biomedical aspects of diabetes management but also its psychosocial determinants, particularly stigma.^[2-5]

Stigma, defined as a socially discrediting attribute that reduces an individual’s social value, has increasingly been recognized as a critical barrier to effective diabetes self-management.^[6-9] People living with diabetes often experience blame, judgment, or exclusion due to public misperceptions that their condition results from personal failure or lifestyle choices. Such stigmatizing attitudes may lead to guilt, shame, and avoidance of medical care, ultimately worsening clinical outcomes.^[10,11] Evidence from diverse chronic conditions, including HIV, epilepsy, obesity, and type 1 diabetes, supports the link between stigma and poor psychological well-being, social isolation, and treatment nonadherence.^[12-15]

Research on stigma in type 2 diabetes mellitus (T2DM) has primarily focused on urban or tertiary care populations in high-income countries. These studies emphasize how public stigma and self-stigma can diminish self-efficacy and impede participation in diabetes education programs.^[11,15] However, very little is known about stigma among adults with T2DM in rural, low-resource settings, particularly in Türkiye, where cultural norms of collectivism and strong family interdependence may uniquely shape perceptions of illness. Rural communities face additional barriers, such as limited healthcare access, lower educational attainment, and economic hardship, all of which can exacerbate both diabetes outcomes and experiences of stigma.^[13,15]

Family functioning represents another important yet underexplored factor. Family support is generally regarded as protective in chronic illness; however, the quality and type of support may vary. In collectivist cultures, excessive involvement or unsolicited advice from family members can paradoxically increase feelings of inadequacy and dependence. Existing research on family functioning and stigma among people with T2DM is scarce, and findings remain inconsistent.^[13,15]

Therefore, this study aimed to evaluate the prevalence and correlates of diabetes-related stigma among adults with T2DM living in rural Türkiye and to examine its relationship with family functioning and disease control.

Methods

Study Design and Setting

A cross-sectional study was conducted between March and May 2025 at a Family Health Center, a rural primary care facility. The study region is characterized by limited access to specialized healthcare services, with primary care centers serving as the main point of care. Mobile health services are not routinely available, and access to healthcare is influenced by both geographic and socioeconomic constraints.

Participants and Sampling

The study population consisted of 279 adults with physician-diagnosed T2DM registered at the center. All were contacted via telephone and invited to participate; 201 individuals consented and completed the study (response rate, 72%). The inclusion criteria were age ≥18 years and a confirmed diagnosis of T2DM. The exclusion criteria included cognitive impairment, severe psychiatric disorders (major depression, psychosis, or bipolar disorder), inability to communicate in Turkish, or physical immobility that precluded participation.

A post hoc power analysis was conducted using G*Power 3.1 software. Assuming a medium effect size (Cohen’s d=0.5), alpha=0.05, and power (1−β)=0.80, the minimum required sample size was calculated as 128 participants. The final sample size of 201 participants exceeded this requirement, indicating sufficient statistical power.

Data Collection Procedures

Data were collected through face-to-face interviews conducted by the same trained investigator to ensure standardization and confidentiality. Each interview lasted approximately 20 minutes and was conducted in a private consultation room. Participants were informed that their responses were confidential and would not influence their clinical care, thereby minimizing social desirability bias.

Measures

Sociodemographic and Clinical Form: A structured questionnaire was developed specifically for this study by the research team, based on previous literature and clinical experience, to collect information on age, sex, marital status, education, occupation, income, family type, number of children, comorbidities, medication and insulin use, HbA1c and fasting plasma glucose (FPG) levels, vaccination history, and attendance at routine follow-ups. Income levels were classified based on self-reported monthly household income relative to the national minimum wage in Türkiye. The English version of this form is provided as Additional File 1.

Diabetes Stigma Assessment Scale-2 (DSAS-2): Perceived stigma was assessed using the DSAS-2, a 19-item validated instrument developed by Brown et al.^[16] and adapted into Turkish by İnkaya et al.^[17] The scale measures perceived stigma across three domains: Treated Differently, Blame and Judgment, and Self-Stigma. Higher scores indicate greater perceived stigma.

Family APGAR Scale: Family functioning was measured using the 5-item Family APGAR Scale, which assesses the dimensions of Adaptability, Partnership, Growth, Affection, and Resolve.^[18,19] Higher scores reflect better family functioning.

Ethical Considerations

This study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Çukurova University Ethics Committee (Decision No. 6, December 2024). Institutional permission was also obtained. Written informed consent was obtained from all participants.

Statistical Analysis

Descriptive statistics were presented as mean±standard deviation (SD) for normally distributed variables and median (interquartile range [IQR]) for non-normally distributed variables. Categorical variables were expressed as frequencies and percentages. Normality was assessed using the Kolmogorov–Smirnov test. Between-group comparisons were performed using t-tests, Mann–Whitney U tests, or chi-square tests, as appropriate. Correlations between continuous variables were assessed using Spearman’s rho. Variables with p<0.05 in univariate analyses and potential confounders with p<0.25 were entered into a multivariate logistic regression model to identify independent predictors of stigma. IBM SPSS Statistics version 20.0 (IBM Corp., Armonk, NY, USA) was used for all analyses. Statistical significance was set at p<0.05.

Results

A total of 201 participants were included in the study. Detailed sociodemographic, clinical, laboratory, and preventive care characteristics are presented in Table 1.

Table 1.

Sociodemographic, Clinical, Laboratory, and Preventive Care Characteristics of Participants (n=201)

Variable	N (%)
Sex, n(%)
Male	94 (46.8%)
Female	107 (53.2%)
Occupation, n(%)
Not working	22 (10.9%)
Housewife	81 (40.3%)
Officer	7 (3.5%)
Worker	27 (13.4%)
Retired	37 (18.4%)
Other	27 (13.4%)
Education, n(%)
Illiterate	48 (23.9%)
Primary education	118 (58.7%)
≥ High school	23 (11.5%)
Marital status, n(%)
Married	171 (85.1%)
Single	6 (3.0%)
Divorced/Widowed	10 (5.0%)
Family type, n(%)
Nuclear	174 (86.6%)
Extended	16 (8.0%)
Separated	2 (1.0%)
Income level, n(%)
Very low / low	176 (87.6%)
Moderate	25 (12.4%)
Having children, n(%)	182 (90.5%)
Number of children, median (25-75p)	4 (2–5)
Comorbidities, n(%)	137 (68.2%)
Hypertension	104 (51.7%)
Hyperlipidemia	85 (42.3%)
Cardiac disease	33 (16.4%)
Psychiatric disorder	17 (8.5%)
Medication use, n(%)
Lipid-lowering medication	137 (68.2%)
Antihypertensive medication	85 (42.3%)
Cardiac Medication	104 (51.7%)
Insulin Use	34 (16.9%)
Diabetes management support, n(%)	36 (17.9%)
Self
Spouse	84 (41.8%)
Children	63 (31.3%)
Relatives	43 (21.4%)
Time since last HbA1c test (months), median (25-75p)	3.0 (1–7)
HbA1c (%), median (25-75p)	7.4 (6.5–8.5)
Time since last glucose test (months), median (25-75p)	3.0 (1–7)
Plasma glucose (mg/dL), median (25-75p)	146.0 (119–190)
Regular Clinic follow-up visits, n (%)
Ophthalmology	97 (48.3%)
Cardiology	64 (32.0%)
Neurology	41 (20.4%)
Nephrology	25 (12.4%)
Vaccinations, n (%)
Any vaccine	47 (23.4%)
Influenza	36 (17.9%)
Tetanus	12 (6.0%)
Pneumococcal	3 (1.5%)
Hepatitis B	2 (1.0%)

HbA1c: Glycated hemoglobin; IQR: Interquartile range. Categorical variables are presented as n (%). Continuous variables are presented as median (IQR), representing the 25th–75th percentile range.

The median time since the last HbA1c and fasting plasma glucose (FPG) measurements was 3 months (IQR: 1–7). Glycemic control was generally suboptimal, with a median HbA1c level of 7.4% (IQR: 6.5–8.5) and a median plasma glucose level of 146 mg/dL (IQR: 119–190).

Specialist follow-up was most frequently reported for ophthalmology and cardiology, whereas neurology and nephrology visits were less common. Preventive care uptake was limited, with only 23.4% of participants reporting any vaccination. Detailed distributions are provided in Table 1.

Evaluation of Family Functioning (Family APGAR)

The median Family APGAR score was 10.0 (IQR: 9.0–10.0), indicating generally high levels of perceived family functioning. When categorized, 88.6% of participants were classified as having high family functioning, while 7.5% and 4.0% were categorized as having moderate and low family functioning, respectively (Table 2).

Table 2.

Family APGAR Scores and Categories

Measure / Category	Median (IQR)
Family APGAR score, median (25-75p)	10.0 (9.0–10.0)
Family APGAR Categories, n (%)
Low functionality	8 (4.0%)
Moderate functionality	15 (7.5%)
High functionality	178 (88.6%)

APGAR: Adaptability, partnership, growth, affection, and resolve; IQR: Interquartile range. Because the Family APGAR score was not normally distributed, it is presented as median (IQR).

Diabetes-Related Stigma (DSAS-2)

The median total DSAS-2 score was 40.0 (IQR: 35.0–45.0), reflecting a moderate level of perceived stigma. Among the subdimensions, the highest variability was observed in the self-stigma domain. Detailed DSAS-2 scores are presented in Table 3.

Table 3.

DSAS-2 (Diabetes Stigma Assessment Scale-2) Scores

Measure	Median (IQR)
Total Stigma Score	40 (35–45)
DSAS-2 Sub-Scale Scores
Stigma–TD (Treated Differently)	12 (10–14)
Stigma–BJ (Blame and Judgment)	16 (14–18)
Stigma–SS (Self-stigma)	12 (10–14)

DSAS-2: Diabetes stigma assessment scale-2; IQR: Interquartile range; TD: Treated differently; BJ: Blame and judgment; SS: Self-stigma. DSAS-2 scores are presented as median (IQR), representing the 25th–75th percentile range.

Correlation Analyses

Correlation analyses demonstrated no significant association between age and total stigma or its subdimensions. However, the number of children showed a weak but statistically significant positive correlation with both the “Treated Differently” (TD) (r=0.202, p=0.006) and self-stigma (r=0.216, p=0.003) subdimensions.

No significant correlations were found between HbA1c levels, fasting plasma glucose levels, or time since the last laboratory measurement and stigma scores. Similarly, family functioning, as measured by the APGAR scale, was not significantly associated with stigma scores (Table 4).

Table 4.

Correlation Analyses Between Sociodemographic, Clinical Parameters and Stigma Scores

Correlates		Total Stigma	Stigma TD	Stigma BJ	Stigma SS
Age (years)	r	0.076	0.062	-0.023	0.134
	p	0.286	0.381	0.743	0.058
Number of children	r	0.157*	0.202*	-00.019	0.216*
	p	0.035*	0.006*	0.802	0.003*
HbA1c (%)	r	-0.056	-0.046	-0.071	0.018
	p	0.431	0.514	0.316	0.802
Fasting glucose (mg/dL)	r	-0.057	-0.025	-0.055	0.000
	p	0.424	0.725	0.439	0.997
Time since HbA1c (months)	r	0.036	0.092	0.061	0.039
	p	0.607	0.195	0.392	0.578
Time since glucose test (months)	r	0.035	0.084	0.068	0.032
	p	0.623	0.234	0.336	0.650
Family APGAR (support)	r	0.024	0.082	0.072	-0.033
	p	0.738	0,245	0,310	0,643

APGAR: Adaptability, partnership, growth, affection, and resolve; BJ: Blame and judgment; HbA1c: Glycated hemoglobin; SS: Self-stigma; TD: Treated differently. Spearman correlation analysis was used. Statistically significant results are shown in bold.

Group Comparisons

Participants with very low income had significantly higher stigma scores than those with moderate income (overall p=0.005). Post hoc analysis with Bonferroni correction confirmed that this difference was significant between the very low- and moderate-income groups (p=0.005).

Stigma scores were also significantly higher among participants using medication and those with comorbid conditions, including hypertension, hyperlipidemia, and heart disease (all p<0.05). No significant differences were observed according to sex, employment status, or education level (all p>0.05).

Logistic Regression Analysis

Participants were dichotomized based on the median total stigma score (<40 vs. ≥40). A multivariate logistic regression model was constructed including variables with p<0.05 in univariate analyses, along with potential confounders (p<0.25). In the final model, income status and medication use emerged as independent predictors of stigma. Medication use was associated with a significantly higher likelihood of stigma (OR: 2.48; 95% CI: 1.23–4.98; p=0.011). Conversely, having a moderate income level was associated with a significantly lower likelihood of stigma than having a very low income (OR: 0.165; 95% CI: 0.048–0.567; p=0.004). Other variables, including age, sex, education level, number of children, follow-up attendance, and insulin use, were not significantly associated with stigma. Detailed regression results are presented in Table 5.

Table 5.

Multivariate Logistic Regression Analysis for Factors Associated with Stigma Presence

Variable	OR	95% CI (Lower–Upper)	p
Age	1.017	0.980–1.056	0.371
Sex (female ref.)	1.173	0.575–2.395	0.661
Income (very low ref.)	0.014
Low	0.494	0.174–1.400	0.184
Moderate	0.165	0.048–0.567	0.004*
Number of children	0.934	0.780–1.118	0.455
Education (no formal ref.)	0.275
Primary–secondary	0.979	0.226–4.243	0.977
High school–university	0.543	0.169–1.752	0.307
Medication use (no ref.)	2.479	1.234–4.982	0.011*
Follow-up (yes ref.)	0.755	0.390–1.462	0.405
Insulin use (no ref.)	1.625	0.681–3.877	0.274

CI: Confidence interval; OR: Odds ratio. Stigma presence was defined according to the median total DSAS-2 score. Statistically significant results are shown in bold.

Discussion

This study examined diabetes-related stigma and its sociodemographic and clinical correlates among adults with type 2 diabetes mellitus (T2DM) living in a rural primary care setting in Türkiye. The main findings indicate that lower income levels, medication use (as a proxy for treatment burden), and the presence of comorbid chronic conditions were independently associated with higher stigma levels. In contrast, family functioning was not significantly associated with stigma, despite generally high Family APGAR scores. Additionally, a modest but significant positive association was observed between the number of children and both the “Treated Differently” and “Self-Stigma” subdimensions.

Our findings are consistent with previous literature demonstrating that diabetes-related stigma is influenced by socioeconomic disadvantage and disease burden.^[20-22] In particular, individuals with lower incomes may experience increased exposure to social judgment and internalized shame, potentially due to perceived social inferiority and limited access to healthcare resources. Similar associations have been reported in diverse settings, where financial constraints and lower health literacy contribute to stigma and reduced engagement with care.^[20-22] Although educational level was not independently associated with stigma in our regression model, its descriptive pattern aligns with earlier studies suggesting that education may play a protective role by improving health literacy and coping strategies.^[10,11]

The observed association between the number of children and self-stigma adds a culturally relevant dimension to the interpretation of our findings. In collectivist societies such as Türkiye, family roles and caregiving responsibilities are strongly emphasized. Chronic illness may interfere with expected parental or familial roles, potentially contributing to feelings of inadequacy or guilt. While prior qualitative studies have highlighted similar themes, our findings provide quantitative support for this relationship in a rural population.^[10] However, this association should be interpreted cautiously given its modest effect size and the cross-sectional design.

Interestingly, family functioning, as measured by the Family APGAR scale, was not significantly associated with stigma levels. This finding appears to contrast with the broader literature emphasizing the beneficial role of social support in chronic disease management.^[23] However, it is important to distinguish between general family cohesion and the qualitative aspects of support. Previous studies have suggested that not all forms of family involvement are beneficial; overprotection, criticism, or unsolicited advice may inadvertently reinforce self-stigma.^[24] In line with this perspective, our results suggest that the presence of family support alone may not be sufficient to mitigate internalized stigma.

Another important finding is the lack of association between glycemic control indicators (HbA1c and fasting glucose levels) and stigma. Although suboptimal glycemic control was observed in the study population, this did not translate into higher stigma scores. This may reflect the influence of structural barriers in rural healthcare settings, including limited access to laboratory services, irregular follow-up, and reduced availability of diabetes education programs. Such systemic factors may play a more prominent role in shaping clinical outcomes than individual-level psychosocial variables alone. Additionally, recent disruptions in healthcare access, including the COVID-19 pandemic and the 2023 Türkiye earthquakes, may have further compounded these challenges.^[25,26]

The association between medication use and higher stigma levels is also noteworthy. This finding likely reflects the broader concept of treatment burden rather than medication use per se. Patients requiring multiple medications or more complex treatment regimens may perceive their illness as more severe or visible, potentially increasing exposure to stigma. Similar observations have been reported in previous studies linking multimorbidity and polypharmacy with increased perceived stigma and a reduced sense of control.^[27-30] Taken together, these findings highlight the multifactorial and context-dependent nature of diabetes-related stigma. In rural settings, stigma appears to be shaped not only by individual clinical factors but also by socioeconomic conditions and sociocultural expectations. The persistence of self-stigma despite relatively high family functioning underscores the need to move beyond traditional support-based approaches and incorporate targeted psychosocial interventions.

Strengths and Limitations

This study provides novel insights into diabetes-related stigma in a relatively underexplored population—adults with T2DM in rural Türkiye—using validated and culturally adapted instruments. The use of face-to-face interviews likely improved data completeness and reliability. However, several limitations should be acknowledged. The cross-sectional design precludes causal inference, and the findings should therefore be interpreted as associative rather than causal. Self-reported measures may be subject to recall and social desirability biases. In addition, the single-center design limits the generalizability of the findings to other rural or urban populations.

Implications for Practice and Policy

The findings of this study have several implications for clinical practice and health policy. First, they highlight the importance of recognizing diabetes-related stigma as a significant psychosocial barrier in primary care settings, particularly in rural areas. Healthcare professionals should be aware of the potential impact of stigma on patient behavior and incorporate stigma-sensitive communication strategies into routine care.

Second, interventions aimed at improving diabetes outcomes should include structured psychoeducational components that address self-stigma, emotional coping, and self-efficacy. While family involvement remains important, our findings suggest that the quality and type of support should be carefully considered.

At the system level, improving access to healthcare services, strengthening community-based support mechanisms, and enhancing health literacy may help reduce the social and psychological burden associated with diabetes. Public health initiatives aimed at reducing misconceptions about diabetes may also contribute to lowering stigma at the community level.

Finally, future research integrating qualitative approaches would be valuable for better understanding the lived experiences of individuals with T2DM in rural contexts and informing culturally tailored interventions.

Conclusions

A significant proportion of adults with T2DM living in rural areas experience multiple dimensions of stigma—most notably self-stigma—arising from socioeconomic hardship, comorbidity, and family role expectations. Although family functioning was generally perceived as strong, it did not adequately buffer against self-blame and internalized shame. These findings highlight that stigma in diabetes is not merely an interpersonal phenomenon but also a structural and cultural issue, particularly in rural communities where collectivism and limited healthcare access intersect.

To address this challenge, primary care interventions should integrate psychosocial and educational components alongside biomedical management. Individual-level approaches, such as structured psychoeducation, self-efficacy enhancement, and peer support groups, can empower patients to reinterpret diabetes as a manageable condition rather than a moral failing. At the system level, training programs for rural healthcare professionals should emphasize stigma recognition, patient-centered communication, and culturally sensitive counseling. Finally, broader public health campaigns aimed at dispelling myths about diabetes causation and treatment may foster empathy, normalize chronic illness, and reduce social blame within rural populations.

Disclosures

Ethics Approval

Ethics committee approval for this study was obtained from the Çukurova University (Approval date: December 6, 2024).

Informed consent

Written informed consent was obtained from all participants prior to data collection.

Conflict of Interest

The authors declare that there is no conflict of interest.

Financial Disclosure

This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Use of AI for Writing Assistance

AI tools (OpenAI, ChatGPT 5.5) were used solely for language editing and proofreading purposes. No generative AI was used to generate, analyze, or interpret the scientific content, data, results, or conclusions of this manuscript.

Authorship Contributions

Concept – M.G., Z.Y.O., Y.K.A.; Design – M.G., Z.Y.O., Y.K.A., S.Y.; Supervision – Z.Y.O., C.O.; Materials − M.G., Z.Y.O.; Data collection &/or processing – M.G., Z.Y.O., Y.K.A., S.Y.; Analysis and/or interpretation – M.G., Z.Y.O., Y.K.A., S.Y.; Literature search – M.G., Z.Y.O., Y.K.A., S.Y., C.O.; Writing – M.G., Z.Y.O., Y.K.A., S.Y., C.O.; Critical review – M.G., Z.Y.O., Y.K.A., S.Y., C.O.

Peer-review

Externally peer-reviewed.