Abstract
Background:
Social support refers to the psychosocial resources available through interpersonal contacts and social networks, which help reduce complications and improve quality of life. It also decreases absenteeism from medical appointments, supports lifestyle changes, and plays a key role in self-management. Evidence on social support among diabetic patients in Ethiopia is limited; therefore, this study aimed to assess its level and associated factors.
Objective:
This study assessed the level of social support and associated factors among diabetic patients.
Study design:
This was an institution-based cross-sectional study design.
Methods:
An institution-based cross-sectional study was conducted, and data were collected from 386 diabetic patients using a systematic random sampling technique. The validated Oslo Social Support Scale was applied to measure the level of social support. The study was conducted March 20 to April 20, 2023 GC. Bivariate and multivariate ordinal logistic regression analyses were performed to identify factors associated with social support. Statistical significance was set at a P-value <0.05.
Result:
This study found that 24.35% (95% CI: 19.9%–27.9%) of the participants had a strong level of social support, and 45.34% (95% CI: 40.5%–50.32%) moderate social support. In multivariable ordinal logistic regression, age, gender, residence, marital status, occupation, and the presence of health insurance were found to be significant predictors of the level of social support.
Conclusion:
Nearly half of the participants reported a moderate level of social support, while about one-fourth had strong social support. Sociodemographic factors such as age, gender, residence, marital status, occupation, and health insurance status significantly influenced the level of social support. Healthcare providers should incorporate social support assessment into routine care to assist individuals with low support. In addition, regional health offices should implement strategies to strengthen social support. Future research should include qualitative and longitudinal studies to better understand patients’ lived experiences and changes in social support over time.
Keywords: diabetes mellitus, family support, social support, support system
Introduction
Diabetes mellitus (DM) is a metabolic disorder characterized by hyperglycemia in the absence of treatment and by the classic symptoms of polyphagia, polyuria, and polydipsia[1]. DM remains a major public health problem worldwide, increasing the risk of infections and worsening the outcomes of certain infectious diseases, such as tuberculosis[2,3]. The financial burden of DM is projected to be 61% higher in 2030 than it was in 2015[4]. DM contributes substantially to the disease burden in sub-Saharan Africa[5]. Its prevalence is increasing significantly in developing countries[6]. In Ethiopia, the burden of DM is considerable and has become a major cause of admission to referral hospitals[7,8].
HIGHLIGHTS.
The study identified varying levels of social support among diabetic patients, ranging from strong to moderate and poor support.
Several sociodemographic factors – including age, gender, residence, marital status, occupation, and health insurance status – were significant predictors of social support levels.
The findings highlight the need for healthcare providers to integrate social support assessment into routine care and for regional health authorities to implement strategies that strengthen social support.
Social support refers to psychosocial asset available in the context of interpersonal contacts and social networks[9]. Despite advances in molecularly targeted therapies and advanced drug delivery strategies such as β-cyclodextrin nanoparticles, biomedical innovations alone cannot ensure optimal patient outcomes[10,11]. For chronic conditions like diabetes, psychosocial factors particularly social support remain essential for improving treatment adherence, self-management, and overall well-being[12].
Social support improves the health outcomes of diabetic patients[13]. It helps reduce complications and improve the quality of life of diabetic patients[14]. It also plays an important role because it helps them manage the disease effectively and has a positive effect on their health[15], and improved social support improved health outcomes in diabetic patients[13]. In addition, the study confirmed that higher social support significantly affects blood glucose monitoring as well as treatment adherence[16–18]. It also reduces medical follow-up absenteeism and helps with lifestyle changes[19]. As a result, it helps prevent chronic and acute complications diabetic[14]. On the other hand, low social support increases the risk of depression in people with type 2 diabetes[20].
In China, 77.93% of diabetic patients had a high level of social support[21]; however, in Kenya only 30.6% reported receiving adequate social support[22]. Social support were found in 95.3% and associated with good glycemic control in Uganda[23]. Majority (80%) had access to various social supports in Nigeria[24]. southern Ethiopia, there was lower level of social support[19]. Generally, Ethiopia has started to support some financial issues like health care insurance, and transportation in case of emergency[25].
The study area’s rapid urbanization, mixed urban–rural patient flow, evolving social support systems, and persistent healthcare access disparities create a unique context where determinants of social support may differ from other Ethiopian settings. However, context-specific evidence remains limited. Understanding social support and its associated factors is crucial for strengthening support systems, improving diabetes management, and preventing complications. Therefore, this study assessed the level of social support and its predictors among diabetic patients to inform policymakers and clinicians.
Methods
Study design
An institution-based cross-sectional study was conducted in three public hospitals from March 20 to April 20, 2023 (GC).
Study area and period
Bahir Dar is administrative of Amhara Regional State. It is situated close to Lake Tana, located 1840 m (6036 feet) above sea level, 565 km (360 miles) northwest of Addis Ababa, Ethiopia. The city has two specialized referral hospitals, and one primary public hospital. This study was conducted public hospitals of Bahir Dar from March 20 to April 20, 2023 GC.
Eligible population
Inclusion criteria
All adult DM patients diagnosed with diabetes, and attending the selected public hospitals during the study period were included.
Exclusion criteria
Patients under 18 years, critically ill, or cognitively impaired were excluded as they could not provide reliable information or informed consent were excluded.
Sample size determination and sampling techniques
The sample size calculation was based on a single population proportion formula by taking of population proportion 50% from previous studies[19], 5% margin of error, and 95% confidence level.
P = 50%:, n = (1.96)2 *0.5*0.5/ (0.05)2 = 384.
After adding a 5% nonresponse rate, the final sample size was 404. Proportional allocation was first applied to the three hospitals. Finally, systematic random sampling was used, based on patients’ appointment registration lists (sampling frame), to select respondents. During the study period, a total of 1211 diabetic patients were registered across the three hospitals. The sampling interval was determined using the formula k = N/n = 3, 1211/404 = 3. The first participant was selected using a lottery method from 1 to 3, and subsequently, every third patient was interviewed.
Study variable
The main outcome variable was the level of social support among diabetic patients. Social support was measured using the Oslo 3-item Social Support Scale (OSS-3). This scale assesses different aspects of social support and is scored as a composite index by summing the responses to each item. The total score ranges from 3 to 14, with higher scores indicating greater social support. Participants who scored 3–8 was classified as poor social support while 9–11 and 12–14 was as moderate and strong social support respectively[26]. The independent variables included sociodemographic factors (age, gender, marital status, residence, health insurance status, occupation, educational status, and monthly income) and clinical characteristics (type of DM, duration of DM, type of treatment, comorbidity status, and blood glucose level).
Data collection tools and procedures
The questionnaire was pre-tested on a 5% sample to assess acceptability and consistency before the actual data collection. The Oslo 3-item Social Support Scale (OSS-3) was used to measure the level of social support among diabetic patients (Supplementary). The tool was translated into Amharic, back-translated, and reviewed by experts to confirm face validity, then pilot-tested among 20 diabetic patients (5% of actual sample size), demonstrating acceptable reliability with a Cronbach alpha of 0.80. The validity of the tool was measured in previous studies in Ethiopia[25,27]. Data were collected through face-to-face interviews conducted by three BSc nurses and supervised by one MSc nurse. Respondents were interviewed, and their medical records were reviewed to extract relevant clinical information when they visited the chronic follow-up clinic for medication refills and/or medical checkups. Data collectors and the supervisor received one day of training on the study objectives and data collection procedures.
Statistical analysis
After verifying the completeness of the raw data, it was entered into EpiData Version 4.6 and exported to SPSS Version 26 for analysis. Descriptive statistics, including means, medians, tables, and figures, were used to summarize the characteristics of the study participants. The dependent variable, social support, was ordinal and categorized as strong, moderate, or poor. Multicollinearity was assessed using the variable inflation factor (VIF), with all values below 2. Model fit was evaluated using goodness-of-fit tests and model fitting information, and the proportional odds assumption was checked using the test of parallel lines. Bi-variable analysis was conducted to identify variables associated with the outcome (P ≤ 0.25), which were then included in the multivariable ordinal logistic regression. Statistical significance was declared at P < 0.05. Adjusted odds ratios (AORs) were used to measure the strength of associations, and potential confounders were controlled for in the multivariable analysis. This study was reported following the STROCSS guidelines[28].
Ethical consideration
Ethical clearance was obtained from the institution review board (IRB) of Bahir Dar University, College of Medicine and Health Sciences with protocol number (BDU762/2023) on January 20, 2023 Bahir Dar, Amhara, Ethiopia. A permission letter was obtained from the medical director and oral permission from chronic follow-up clinic focal person of each hospital. Each respondent was asked about their voluntariness before the interview. The name of the patient was not be mentioned to ensure the privacy of patients, and confidentiality was maintained throughout the study.
Result
Sociodemographic characteristics of respondents
Out of the 404 sampled participants, 386 completed the study, yielding a response rate of 95.55%. The mean age of respondents was 42.3 years (SD = 13.99), ranging from 18 to 75 years. More than half of the participants, 211 (54.7%), were male, and the majority, 289 (74.9%), resided in urban areas. Most participants (59.3%) were married, while 16.6% were single. Regarding education, 15% had completed primary school, and 16.6% were graduates (Table 1).
Table 1.
Sociodemographic characteristics of diabetic Patients in Ethiopia, 2023; n = 386
| Variable | Category | Frequency | Percent |
|---|---|---|---|
| Gender | Male | 211 | 54.7 |
| Female | 175 | 45.3 | |
| Age | Less or equal 45 | 219 | 56.7 |
| Above 45 | 167 | 43.3 | |
| Residence | Urban | 289 | 74.9 |
| Rural | 97 | 25.1 | |
| Marital status | Married | 229 | 59.3 |
| Single | 64 | 16.6 | |
| Widowed | 50 | 13 | |
| Divorce | 43 | 11.1 | |
| Education | College and above | 64 | 16.6 |
| Grades 9–12 | 89 | 23.1 | |
| Primary[1-8] | 58 | 15 | |
| No formal education | 175 | 45.3 | |
| Occupation | Private business | 106 | 27.5 |
| Government employee | 88 | 22.8 | |
| Private employee | 75 | 19.4 | |
| Other(student, daily laborer, retired) | 117 | 30.3 | |
| Mode of payment | Self | 194 | 50.3 |
| Health insurance | 192 | 49.7 | |
| Income | <1000birr | 51 | 13.2 |
| 1001–3000birr | 102 | 26.4 | |
| 3001–5000birr | 76 | 19.7 | |
| >5000birr | 157 | 40.7 |
Clinical characteristics of respondents
In this study, more than half of the participants (56%) had type 2 diabetes, and most (64.2%) had controlled blood glucose levels. Additionally, 19.4% of the participants had comorbidities other than diabetes (Table 2).
Table 2.
Clinical characteristics of DM patients attending chronic follow-up clinics in Ethiopia, 2023; n = 386
| Variable | Category | Frequency | Percent |
|---|---|---|---|
| Comorbidity | Yes | 75 | 19.4 |
| No | 311 | 80.6 | |
| Type of DM | Type1 | 170 | 44 |
| Type2 | 216 | 56 | |
| DM duration | >10 years | 114 | 29.5 |
| 5–10 years | 140 | 36.3 | |
| <5 years | 132 | 34.2 | |
| Glycemic status | Good control | 248 | 64.2 |
| Poor control | 138 | 35.8 | |
| Type of treatment | Insulin | 186 | 48.2 |
| Oral antiglycemic | 155 | 40.2 | |
| Both oral and insulin | 45 | 11.7 |
Assumption testing
In model fitting, a significance value less than 0.05 indicates that the model is statistically significant. Therefore, we reject the null hypothesis. The baseline model, which includes no independent variables, and the final model, which includes all potential independent variables, did not differ significantly according to the null hypothesis. In this study, the final model had a significance value of P < 0.05, indicating that it was a good fit for the data.
Goodness-of-fit test
The Pearson significance value was used to assess the goodness-of-fit of the model. For a model to fit the data well, a P-value greater than 0.05 is required. In this study, the Pearson P-value was 0.137, indicating that the logit model provided an adequate fit for the observed data.
Test of parallel line
This test examines whether the relationship between each explanatory variable and the dependent variable (level of social support) is consistent across response categories. The null hypothesis states that the slope coefficients are equal across response categories. In this study, the test of parallel lines yielded a P-value of 0.08, which is greater than 0.05. Therefore, the null hypothesis was accepted, indicating that the proportional odds assumption was satisfied.
Prevalence of social support among diabetic patients
Nearly one-fourth of the participants, 94 (24.35%, 95% CI: 19.9%–27.9%), had a strong level of social support, followed by 175 (45.34%, 95% CI: 40.5%–50.3%) who had a moderate level of social support (Fig. 1). The mean score of social support among diabetic patients were 9.55 ± 2.32.
Figure 1.
The distribution of social support among diabetic patients in Bahir Dar city public hospitals, Ethiopia, 2023.
Factor associated with level of social support
In bivariate ordinal logistic regression, gender, age, educational level, residence, marital status, level of income, health insurance status, presence of comorbidity, occupational status, and blood glucose status were fitted. In multivariable ordinal logistic regression, age, gender, residence, marital status, occupational status, and the presence of health insurance were found to be significant predictors of the level of social support. Respondents aged ≤45 years were 2.48 times more likely to have strong social support compared to those older than 45 years (AOR = 2.48, 95% CI: 1.57–3.92), indicating a negative association between increasing age and strong social support. Urban residents were more likely to have strong social support than rural residents (AOR = 1.92, 95% CI: 1.12–3.23), showing a positive association between living in an urban area and social support. Regarding marital status, single participants had 70% lower odds of strong social support compared to divorced individuals (AOR = 0.30, 95% CI: 0.13–0.69). Participants with health insurance were 2.27 times more likely to have strong social support than those without insurance (AOR = 2.27, 95% CI: 1.51–3.42), indicating a positive association between having health insurance and social support. Occupational status was also a significant predictor; government employees had 2.1 times higher odds of strong social support compared to students, farmers, and housewives. Additionally, male participants were more likely to have strong social support than females (AOR = 1.71, 95% CI: 1.11–2.63), suggesting a positive association between male gender and social support (Table 3).
Table 3.
Factors associated with level of social support among diabetic patients in Ethiopia, 2023; n = 386
| Variable | Social support | COR | AOR 95% | P-value | |||
|---|---|---|---|---|---|---|---|
| Poor | Moderate | Strong | |||||
| Gender | Male | 54 | 99 | 58 | 1.35 (1.07–2.27) | 1.71 (1.11–2.63) | 0.015 |
| female | 63 | 76 | 36 | 1 | 1 | ||
| Age | Less or equal 45 | 45 | 95 | 69 | 2.06 (1.4–6.72) | 2.48 (1.57–3.92) | 0.000 |
| Above 45 | 62 | 80 | 25 | Ref | 1 | ||
| Education | College and above | 18 | 20s | 26 | 2.3 (1.34–3.96) | 1.45 (0.78–2.55) | 0.248 |
| Grade 9–12 | 20 | 47 | 22 | 1.71 (1.06–2.76) | 1.22 (0.72–2.06) | 0.470 | |
| Grade 1–8 | 15 | 28 | 15 | 1.62 (0.93–2.83) | 1.4 (0.78–2.53) | 0.263 | |
| No formal education | 64 | 80 | 31 | Ref | 1 | ||
| Residence | Urban | 76 | 139 | 74 | 1.75 (1.14–2.71) | 1.92 (1.12–3.23) | 0.014 |
| Rural | 41 | 36 | 20 | Ref | 1 | ||
| Marital status | Married | 59 | 110 | 60 | 1.29 (0.70–2.36) | 0.89 (0.46–1.72) | 0.724 |
| Single | 32 | 21 | 11 | 0.52 (0.25–1.07) | 0.30 (0.13–0.69) | 0.005 | |
| Widowed | 12 | 25 | 13 | 1.34 (0.63–2.86) | 1.3 (0.58–2.9) | 0.727 | |
| Divorce | 14 | 19 | 10 | Ref | 1 | ||
| Income | <1000birr | 16 | 19 | 16 | 0.88 (0.49–1.59) | 2.07 (0.97–4.4) | 0.060 |
| 1001–3000birr | 46 | 39 | 17 | 0.41 (0.26–0.66) | 0.70 (0.41–1.22) | 0.211 | |
| 3001–5000birr | 21 | 36 | 19 | 0.82 (0.49–1.36) | 1.36 (0.78–2.39) | 0.278 | |
| >5000birr | 34 | 81 | 42 | Ref | 1 | 1 | |
| Occupation | Private business | 31 | 48 | 27 | 1.80 (1.09–2.95) | 1.33 (0.72–2.45) | 0.360 |
| Government employee | 16 | 41 | 31 | 3.06 (1.80–5.20) | 2.10 (1.07–4.15) | 0.032 | |
| Private employee | 22 | 34 | 19 | 1.78 (1.04–3.08) | 1.25 (0.65–2.42) | 0.505 | |
| Other(housewife, student, farmer) | 48 | 52 | 17 | Ref | 1 | 1 | |
| Health insurance | Yes | 49 | 87 | 58 | 1.72 (1.18–2.50) | 2.27 (1.51–3.42) | 0.000 |
| No | 68 | 88 | 36 | Ref | 1 | ||
| Glycemic status | Good control | 68 | 109 | 71 | 1.65 (1.12–2.44) | 1.37 (0.91–2.08) | 0.136 |
| Poor control | 49 | 66 | 23 | Ref | Ref | ||
| Comorbidity | Yes | 33 | 27 | 15 | 0.55 (0.34-0.88) | 0.81 (0.47–1.41) | 0.463 |
| No | 84 | 148 | 79 | ref | 1 | ||
Note: Birr is Ethiopian local currency
Discussion
While advances in genomics and proteomics are transforming drug discovery and personalized therapy[29], psychosocial factors especially, social support remain crucial for effective diabetes management. It is important for nurses to consider during counseling about self-care[30]. In this study, 24.35% of participants had a strong level of social support, while 45.34% had moderate support. In contrast, a study in Kenya reported a higher level of strong social support at 30.6%[31]. This discrepancy may be attributed to differences in educational status, as 88.8% of participants in the Kenyan study had some form of formal education compared to only 54.7% in our study. Education can enhance awareness of available support networks and improve the ability to seek and utilize social resources. Furthermore, the study area lacks well-established social support systems beyond healthcare insurance[25], which may limit patients’ access to emotional, informational, and practical support. The relatively low level of strong social support observed in this study underscores the need for interventions to strengthen social support structures, and integrate community- and family-based support into diabetes care programs to improve adherence, self-management, and overall health outcomes[32,33].
In this study, there was a significant difference in the level of social support between age categories. Respondents with an age less than or equal to 45 years of age had better social support than older age groups. The finding was supported by previous studies done in Mashhad[34] and in China[35]. This was because younger people were more likely to build social networks and get better social support. This age-related disparity suggests the need for targeted interventions to strengthen social support for older diabetic patients[36].
The study found that males were more likely to have higher social support than females, which was supported by a previous study done in Iran[37] and India[38]. While it is in contrast with the findings of Uganda[23]. This is because women have a greater responsibility to care for the entire family, while women do not equally benefit from social support. Additionally, cultural norms may prioritize men’s social interactions, leading to greater visibility and access to support for males compared to females[39]. Addressing these barriers can improve women’s access to support and enhance their treatment outcomes.
According to marital status, single respondents were less likely to have a higher level of social support. The result was in agreement with previous studies done in public hospitals in Greece, Iran, and Myanmar[37,40,41]. A possible explanation is that married individuals often receive emotional, financial, and practical assistance from their spouses and extended family, whereas single individuals may lack consistent support from close household members, resulting in lower overall social support[19].
There were significant differences in level of social support between those with health insurance and those without health insurance. Respondents with health insurance were more likely to have a high level of social support compared to those without health insurance the result was in line with findings of India[38] and Nigeria[42]. One possible justification is that individuals with health insurance are more likely to be engaged with the health system, have better access to healthcare services, and receive more guidance from providers[43].
Occupational status was also isolated as a predictor. Respondents with government employment received more social support than others (students, farmers, and housewives). The result was in line with a similar study in Greece[40,44] and India[38]. Government-employed respondents may develop social networks with colleagues that enhance social support. Additionally, they may experience higher support due to job stability and greater health awareness[45,46].
Urban residents were more likely to have strong social support than rural residents. Other research results also reported similar findings in Uganda[17] and southern Ethiopia[19]. This may be because health-seeking behavior and health literacy tend to be higher in urban areas[47]. Another possible justification is that urban areas provide diverse social networks, better access to services, and more opportunities for social interaction, which together foster stronger social ties[48]. Targeted interventions are needed for rural populations to strengthen social support through improved health education, community engagement, and access to support networks[49]. Community support groups particularly in rural areas along with strengthened diabetes education through health extension workers may collectively enhance overall social support.
Strength and limitation
The strength of this study was the fact that primary data was used. This was also the first study in the study area. Because this study was cross-sectional, the observed associations cannot be interpreted as causal relationships.
Conclusions and recommendations
The paper assesses the level of social support and associated factors, which are very important for patient care counselling. Nearly half of the participants reported a moderate level of social support, while about one-fourth had strong social support. Sociodemographic factors such as age, gender, residence, marital status, occupation, and health insurance status significantly influenced the level of social support. These findings highlight the need for targeted interventions to enhance social support, particularly among groups with lower support levels. Strengthening social support systems should therefore be a clinical priority to improve patient outcomes and enhance the overall quality of diabetes management. Thus healthcare providers should integrate social support assessment into routine patient care to identify individuals at risk of low support and provide appropriate psychosocial interventions. The regional health office should also develop strategies to strengthen social support among diabetic patients. Future research should include qualitative and longitudinal studies to better understand patients’ lived experiences and changes in social support over time.
Footnotes
Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.
Contributor Information
Bekalu Mekonen Belay, Email: bekalumekonen20@gmail.com.
Yeshiambaw Eshetie, Email: yeshiambaweshetie@gmail.com.
Mengistu Ewunetu, Email: mengistue11@gmail.com.
Melese Kebede Hailu, Email: meleske143@gmail.com.
Ayenew Genet Kebede, Email: ayenewgenetk@gmail.com.
Yirgalem Abere, Email: yirgalemabere12@gmail.com.
Study area and period
Bahir Dar is administrative of Amhara Regional State. It is situated close to Lake Tana, located 1840m (6036 feet) above sea level, 565 km (360 miles) northwest of Addis Ababa, Ethiopia. The city has two specialized referral hospitals, and one primary public hospital. This study was conducted public hospitals of Bahir Dar from March 20 to April 20, 2023 GC.
Ethical approval
Ethical approval for this study was provided by the Ethical Committee of Bahir Dar University, College of Medicine and Health Sciences with protocol number (BDU762/2023) on 20 January 2023 Bahir Dar, Amhara, Ethiopia.
Source of funding
Not Applicable.
Author contributions
B.M.B., Y.E., and M.K.H.: contributed to proposal development, data collector training, data analysis, interpretation, and reporting. A.G.K., Y.A., and M.E.: contributed to proposal revision, study design, result interpretation, and reporting. All authors contributed to manuscript writing and approved the final version.
Conflicts of interest disclosure
N/A.
Acknowledgements
The authors thank Felege Hiwot Referral Hospital, Tibebe Ghion Specialized Hospital, and Addis Alem Primary Hospital for their cooperation, and acknowledge the data collectors, supervisors, and study participants for their valuable contributions.
Research registration unique identifying number (UIN)
The protocol has been registered in ClinicalTrials.gov with ID NCT07010731 found in the link https://register.clinicaltrials.gov/prs/beta/records
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