thesis about diabetes mellitus

• Previous Article
• Next Article

Research Design and Methods

Article information, literature review of type 2 diabetes management and health literacy.

• Split-Screen
• Article contents
• Figures & tables
• Supplementary Data
• Peer Review
• Open the PDF for in another window
• Cite Icon Cite
• Get Permissions

Rulla Alsaedi , Kimberly McKeirnan; Literature Review of Type 2 Diabetes Management and Health Literacy. Diabetes Spectr 1 November 2021; 34 (4): 399–406. https://doi.org/10.2337/ds21-0014

Download citation file:

• Ris (Zotero)
• Reference Manager

The purpose of this literature review was to identify educational approaches addressing low health literacy for people with type 2 diabetes. Low health literacy can lead to poor management of diabetes, low engagement with health care providers, increased hospitalization rates, and higher health care costs. These challenges can be even more profound among minority populations and non-English speakers in the United States.

A literature search and standard data extraction were performed using PubMed, Medline, and EMBASE databases. A total of 1,914 articles were identified, of which 1,858 were excluded based on the inclusion criteria, and 46 were excluded because of a lack of relevance to both diabetes management and health literacy. The remaining 10 articles were reviewed in detail.

Patients, including ethnic minorities and non-English speakers, who are engaged in diabetes education and health literacy improvement initiatives and ongoing follow-up showed significant improvement in A1C, medication adherence, medication knowledge, and treatment satisfaction. Clinicians considering implementing new interventions to address diabetes care for patients with low health literacy can use culturally tailored approaches, consider ways to create materials for different learning styles and in different languages, engage community health workers and pharmacists to help with patient education, use patient-centered medication labels, and engage instructors who share cultural and linguistic similarities with patients to provide educational sessions.

This literature review identified a variety of interventions that had a positive impact on provider-patient communication, medication adherence, and glycemic control by promoting diabetes self-management through educational efforts to address low health literacy.

Diabetes is the seventh leading cause of death in the United States, and 30.3 million Americans, or 9.4% of the U.S. population, are living with diabetes ( 1 , 2 ). For successful management of a complicated condition such as diabetes, health literacy may play an important role. Low health literacy is a well-documented barrier to diabetes management and can lead to poor management of medical conditions, low engagement with health care providers (HCPs), increased hospitalizations, and, consequently, higher health care costs ( 3 – 5 ).

The Healthy People 2010 report ( 6 ) defined health literacy as the “degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions.” Diabetes health literacy also encompasses a wide range of skills, including basic knowledge of the disease state, self-efficacy, glycemic control, and self-care behaviors, which are all important components of diabetes management ( 3 – 5 , 7 ). According to the Institute of Medicine’s Committee on Health Literacy, patients with poor health literacy are twice as likely to have poor glycemic control and were found to be twice as likely to be hospitalized as those with adequate health literacy ( 8 ). Associations between health literacy and health outcomes have been reported in many studies, the first of which was conducted in 1995 in two public hospitals and found that many patients had inadequate health literacy and could not perform the basic reading tasks necessary to understand their treatments and diagnoses ( 9 ).

Evaluation of health literacy is vital to the management and understanding of diabetes. Several tools for assessing health literacy have been evaluated, and the choice of which to use depends on the length of the patient encounter and the desired depth of the assessment. One widely used literacy assessment tool, the Test of Functional Health Literacy in Adults (TOFHLA), consists of 36 comprehension questions and four numeric calculations ( 10 ). Additional tools that assess patients’ reading ability include the Rapid Estimate of Adult Literacy in Medicine (REALM) and the Literacy Assessment for Diabetes. Tests that assess diabetes numeracy skills include the Diabetes Numeracy Test, the Newest Vital Sign (NVS), and the Single-Item Literacy Screener (SILS) ( 11 ).

Rates of both diabetes and low health literacy are higher in populations from low socioeconomic backgrounds ( 5 , 7 , 12 ). People living in disadvantaged communities face many barriers when seeking health care, including inconsistent housing, lack of transportation, financial difficulties, differing cultural beliefs about health care, and mistrust of the medical professions ( 13 , 14 ). People with high rates of medical mistrust tend to be less engaged in their care and to have poor communication with HCPs, which is another factor HCPs need to address when working with their patients with diabetes ( 15 ).

The cost of medical care for people with diabetes was $327 billion in 2017, a 26% increase since 2012 ( 1 , 16 ). Many of these medical expenditures are related to hospitalization and inpatient care, which accounts for 30% of total medical costs for people with diabetes ( 16 ).

People with diabetes also may neglect self-management tasks for various reasons, including low health literacy, lack of diabetes knowledge, and mistrust between patients and HCPs ( 7 , 15 ).

These challenges can be even more pronounced in vulnerable populations because of language barriers and patient-provider mistrust ( 17 – 19 ). Rates of diabetes are higher among racial and ethnic minority groups; 15.1% of American Indians and Alaskan Natives, 12.7% of Non-Hispanic Blacks, 12.1% of Hispanics, and 8% of Asian Americans have diagnosed diabetes, compared with 7.4% of non-Hispanic Whites ( 1 ). Additionally, patient-provider relationship deficits can be attributed to challenges with communication, including HCPs’ lack of attention to speaking slowly and clearly and checking for patients’ understanding when providing education or gathering information from people who speak English as a second language ( 15 ). White et al. ( 15 ) demonstrated that patients with higher provider mistrust felt that their provider’s communication style was less interpersonal and did not feel welcome as part of the decision-making process.

To the authors’ knowledge, there is no current literature review evaluating interventions focused on health literacy and diabetes management. There is a pressing need for such a comprehensive review to provide a framework for future intervention design. The objective of this literature review was to gather and summarize studies of health literacy–based diabetes management interventions and their effects on overall diabetes management. Medication adherence and glycemic control were considered secondary outcomes.

Search Strategy

A literature review was conducted using the PubMed, Medline, and EMBASE databases. Search criteria included articles published between 2015 and 2020 to identify the most recent studies on this topic. The search included the phrases “diabetes” and “health literacy” to specifically focus on health literacy and diabetes management interventions and was limited to original research conducted in humans and published in English within the defined 5-year period. Search results were exported to Microsoft Excel for evaluation.

Study Selection

Initial screening of the articles’ abstracts was conducted using the selection criteria to determine which articles to include or exclude ( Figure 1 ). The initial search results were reviewed for the following inclusion criteria: original research (clinical trials, cohort studies, and cross-sectional studies) conducted in human subjects with type 2 diabetes in the United States, and published in English between 2015 and 2020. Articles were considered to be relevant if diabetes was included as a medical condition in the study and an intervention was made to assess or improve health literacy. Studies involving type 1 diabetes or gestational diabetes and articles that were viewpoints, population surveys, commentaries, case reports, reviews, or reports of interventions conducted outside of the United States were excluded from further review. The criteria requiring articles to be from the past 5 years and from the United States were used because of the unique and quickly evolving nature of the U.S. health care system. Articles published more than 5 years ago or from other health care systems may have contributed information that was not applicable to or no longer relevant for HCPs in the United States. Articles were screened and reviewed independently by both authors. Disagreements were resolved through discussion to create the final list of articles for inclusion.

PRISMA diagram of the article selection process.

Data Extraction

A standard data extraction was performed for each included article to obtain information including author names, year of publication, journal, study design, type of intervention, primary outcome, tools used to assess health literacy or type 2 diabetes knowledge, and effects of intervention on overall diabetes management, glycemic control, and medication adherence.

A total of 1,914 articles were collected from a search of the PubMed, MEDLINE, and EMBASE databases, of which 1,858 were excluded based on the inclusion and exclusion criteria. Of the 56 articles that met criteria for abstract review, 46 were excluded because of a lack of relevance to both diabetes management and health literacy. The remaining 10 studies identified various diabetes management interventions, including diabetes education tools such as electronic medication instructions and text message–based interventions, technology-based education videos, enhanced prescription labels, learner-based education materials, and culturally tailored interventions ( 15 , 20 – 28 ). Figure 1 shows the PRISMA diagram of the article selection process, and Table 1 summarizes the findings of the article reviews ( 15 , 20 – 28 ).

Findings of the Article Reviews (15,20–28)

SAHLSA, Short Assessment of Health Literacy for Spanish Adults.

Medical mistrust and poor communication are challenging variables in diabetes education. White et al. ( 15 ) examined the association between communication quality and medical mistrust in patients with type 2 diabetes. HCPs at five health department clinics received training in effective health communication and use of the PRIDE (Partnership to Improve Diabetes Education) toolkit in both English and Spanish, whereas control sites were only exposed to National Diabetes Education Program materials without training in effective communication. The study evaluated participant communication using several tools, including the Communication Assessment Tool (CAT), Interpersonal Processes of Care (IPC-18), and the Short Test of Functional Health Literacy in Adults (s-TOFHLA). The authors found that higher levels of mistrust were associated with lower CAT and IPC-18 scores.

Patients with type 2 diabetes are also likely to benefit from personalized education delivery tools such as patient-centered labeling (PCL) of prescription drugs, learning style–based education materials, and tailored text messages ( 24 , 25 , 27 ). Wolf et al. ( 27 ) investigated the use of PCL in patients with type 2 diabetes and found that patients with low health literacy who take medication two or more times per day have higher rates of proper medication use when using PCL (85.9 vs. 77.4%, P = 0.03). The objective of the PCL intervention was to make medication instructions and other information on the labels easier to read to improve medication use and adherence rates. The labels incorporated best-practice strategies introduced by the Institute of Medicine for the Universal Medication Schedule. These strategies prioritize medication information, use of larger font sizes, and increased white space. Of note, the benefits of PCL were largely seen with English speakers. Spanish speakers did not have substantial improvement in medication use or adherence, which could be attributed to language barriers ( 27 ).

Nelson et al. ( 25 ) analyzed patients’ engagement with an automated text message approach to supporting diabetes self-care activities in a 12-month randomized controlled trial (RCT) called REACH (Rapid Education/Encouragement and Communications for Health) ( 25 ). Messages were tailored based on patients’ medication adherence, the Information-Motivation-Behavioral Skills model of health behavior change, and self-care behaviors such as diet, exercise, and self-monitoring of blood glucose. Patients in this trial were native English speakers, so further research to evaluate the impact of the text message intervention in patients with limited English language skills is still needed. However, participants in the intervention group reported higher engagement with the text messages over the 12-month period ( 25 ).

Patients who receive educational materials based on their learning style also show significant improvement in their diabetes knowledge and health literacy. Koonce et al. ( 24 ) developed and evaluated educational materials based on patients’ learning style to improve health literacy in both English and Spanish languages. The materials were made available in multiple formats to target four different learning styles, including materials for visual learners, read/write learners, auditory learners, and kinesthetic learners. Spanish-language versions were also available. Researchers were primarily interested in measuring patients’ health literacy and knowledge of diabetes. The intervention group received materials in their preferred learning style and language, whereas the control group received standard of care education materials. The intervention group showed significant improvement in diabetes knowledge and health literacy, as indicated by Diabetes Knowledge Test (DKT) scores. More participants in the intervention group reported looking up information about their condition during week 2 of the intervention and showed an overall improvement in understanding symptoms of nerve damage and types of food used to treat hypoglycemic events. However, the study had limited enrollment of Spanish speakers, making the applicability of the results to Spanish-speaking patients highly variable.

Additionally, findings by Hofer et al. ( 22 ) suggest that patients with high A1C levels may benefit from interventions led by community health workers (CHWs) to bridge gaps in health literacy and equip patients with the tools to make health decisions. In this study, Hispanic and African American patients with low health literacy and diabetes not controlled by oral therapy benefited from education sessions led by CHWs. The CHWs led culturally tailored support groups to compare the effects of educational materials provided in an electronic format (via iDecide) and printed format on medication adherence and self-efficacy. The study found increased adherence with both formats, and women, specifically, had a significant increase in medication adherence and self-efficacy. One of the important aspects of this study was that the CHWs shared cultural and linguistic characteristics with the patients and HCPs, leading to increased trust and satisfaction with the information presented ( 22 ).

Kim et al. ( 23 ) found that Korean-American participants benefited greatly from group education sessions that provided integrated counseling led by a team of nurses and CHW educators. The intervention also had a health literacy component that focused on enhancing skills such as reading food package labels, understanding medical terminology, and accessing health care services. This intervention led to a significant reduction of 1–1.3% in A1C levels in the intervention group. The intervention established the value of collaboration between CHW educators and nurses to improve health information delivery and disease management.

A collaboration between CHW educators and pharmacists was also shown to reinforce diabetes knowledge and improve health literacy. Sharp et al. ( 26 ) conducted a cross-over study in four primary care ambulatory clinics that provided care for low-income patients. The study found that patients with low health literacy had more visits with pharmacists and CHWs than those with high health literacy. The CHWs provided individualized support to reinforce diabetes self-management education and referrals to resources such as food, shelter, and translation services. The translation services in this study were especially important for building trust with non-English speakers and helping patients understand their therapy. Similar to other studies, the CHWs shared cultural and linguistic characteristics with their populations, which helped to overcome communication-related and cultural barriers ( 23 , 26 ).

The use of electronic tools or educational videos yielded inconclusive results with regard to medication adherence. Graumlich et al. ( 20 ) implemented a new medication planning tool called Medtable within an electronic medical record system in several outpatient clinics serving patients with type 2 diabetes. The tool was designed to organize medication review and patient education. Providers can use this tool to search for medication instructions and actionable language that are appropriate for each patient’s health literacy level. The authors found no changes in medication knowledge or adherence, but the intervention group reported higher satisfaction. On the other hand, Yeung et al. ( 28 ) showed that pharmacist-led online education videos accessed using QR codes affixed to the patients’ medication bottles and health literacy flashcards increased patients’ medication adherence in an academic medical hospital.

Goessl et al. ( 21 ) found that patients with low health literacy had significantly higher retention of information when receiving evidence-based diabetes education through a DVD recording than through an in-person group class. This 18-month RCT randomized participants to either the DVD or in-person group education and assessed their information retention through a teach-back strategy. The curriculum consisted of diabetes prevention topics such as physical exercise, food portions, and food choices. Participants in the DVD group had significantly higher retention of information than those in the control (in-person) group. The authors suggested this may have been because participants in the DVD group have multiple opportunities to review the education material.

Management of type 2 diabetes remains a challenge for HCPs and patients, in part because of the challenges discussed in this review, including communication barriers between patients and HCPs and knowledge deficits about medications and disease states ( 29 ). HCPs can have a positive impact on the health outcomes of their patients with diabetes by improving patients’ disease state and medication knowledge.

One of the common themes identified in this literature review was the prevalence of culturally tailored diabetes education interventions. This is an important strategy that could improve diabetes outcomes and provide an alternative approach to diabetes self-management education when working with patients from culturally diverse backgrounds. HCPs might benefit from using culturally tailored educational approaches to improve communication with patients and overcome the medical mistrust many patients feel. Although such mistrust was not directly correlated with diabetes management, it was noted that patients who feel mistrustful tend to have poor communication with HCPs ( 20 ). Additionally, Latino/Hispanic patients who have language barriers tend to have poor glycemic control ( 19 ). Having CHWs work with HCPs might mitigate some patient-provider communication barriers. As noted earlier, CHWs who share cultural and linguistic characteristics with their patient populations have ongoing interactions and more frequent one-on-one encounters ( 12 ).

Medication adherence and glycemic control are important components of diabetes self-management, and we noted that the integration of CHWs into the diabetes health care team and the use of simplified medication label interventions were both successful in improving medication adherence ( 23 , 24 ). The use of culturally tailored education sessions and the integration of pharmacists and CHWs into the management of diabetes appear to be successful in reducing A1C levels ( 12 , 26 ). Electronic education tools and educational videos alone did not have an impact on medication knowledge or information retention in patients with low health literacy, but a combination of education tools and individualized sessions has the potential to improve diabetes medication knowledge and overall self-management ( 20 , 22 , 30 ).

There were several limitations to our literature review. We restricted our search criteria to articles published in English and studies conducted within the United States to ensure that the results would be relevant to U.S. HCPs. However, these limitations may have excluded important work on this topic. Additional research expanding this search beyond the United States and including articles published in other languages may demonstrate different outcomes. Additionally, this literature review did not focus on A1C as the primary outcome, although A1C is an important indicator of diabetes self-management. A1C was chosen as the method of evaluating the impact of health literacy interventions in patients with diabetes, but other considerations such as medication adherence, impact on comorbid conditions, and quality of life are also important factors.

The results of this work show that implementing health literacy interventions to help patients manage type 2 diabetes can have beneficial results. However, such interventions can have significant time and monetary costs. The potential financial and time costs of diabetes education interventions were not evaluated in this review and should be taken into account when designing interventions. The American Diabetes Association estimated the cost of medical care for people with diabetes to be $327 billion in 2017, with the majority of the expenditure related to hospitalizations and nursing home facilities ( 16 ). Another substantial cost of diabetes that can be difficult to measure is treatment for comorbid conditions and complications such as cardiovascular and renal diseases.

Interventions designed to address low health literacy and provide education about type 2 diabetes could be a valuable asset in preventing complications and reducing medical expenditures. Results of this work show that clinicians who are considering implementing new interventions may benefit from the following strategies: using culturally tailored approaches, creating materials for different learning styles and in patients’ languages, engaging CHWs and pharmacists to help with patient education, using PCLs for medications, and engaging education session instructors who share patients’ cultural and linguistic characteristics.

Diabetes self-management is crucial to improving health outcomes and reducing medical costs. This literature review identified interventions that had a positive impact on provider-patient communication, medication adherence, and glycemic control by promoting diabetes self-management through educational efforts to address low health literacy. Clinicians seeking to implement diabetes care and education interventions for patients with low health literacy may want to consider drawing on the strategies described in this article. Providing culturally sensitive education that is tailored to patients’ individual learning styles, spoken language, and individual needs can improve patient outcomes and build patients’ trust.

Duality of Interest

No potential conflicts of interest relevant to this article were reported.

Author Contributions

Both authors conceptualized the literature review, developed the methodology, analyzed the data, and wrote, reviewed, and edited the manuscript. R.A. collected the data. K.M. supervised the review. K.M. is the guarantor of this work and, as such, has full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation

Portions of this research were presented at the Washington State University College of Pharmacy and Pharmaceutical Sciences Honors Research Day in April 2019.

Email alerts

• Online ISSN 1944-7353
• Print ISSN 1040-9165
• Diabetes Care
• Clinical Diabetes
• Diabetes Spectrum
• Standards of Medical Care in Diabetes
• Scientific Sessions Abstracts
• BMJ Open Diabetes Research & Care
• ShopDiabetes.org
• ADA Professional Books

Clinical Compendia

• Clinical Compendia Home
• Latest News
• DiabetesPro SmartBrief
• Special Collections
• DiabetesPro®
• Diabetes Food Hub™
• Insulin Affordability
• Know Diabetes By Heart™
• About the ADA
• Journal Policies
• For Reviewers
• Advertising in ADA Journals
• Reprints and Permission for Reuse
• Copyright Notice/Public Access Policy
• ADA Professional Membership
• ADA Member Directory
• Diabetes.org
• X (Twitter)
• Cookie Policy
• Accessibility
• Terms & Conditions
• Get Adobe Acrobat Reader
• © Copyright American Diabetes Association

This Feature Is Available To Subscribers Only

Sign In or Create an Account

• Open access
• Published: 10 March 2020

Health-related quality of life and associated factors among patients with diabetes mellitus at the University of Gondar referral hospital

• Andualem Yalew Aschalew 1 ,
• Mezgebu Yitayal 1 &
• Amare Minyihun 1  

Health and Quality of Life Outcomes volume  18 , Article number:  62 ( 2020 ) Cite this article

10k Accesses

38 Citations

8 Altmetric

Metrics details

Diabetes mellitus, which has a wide range of effects on the physical, social and psychological aspects of the well-being of a person, is a common and challenging chronic disease that causes a significant rate of morbidity and mortality. However, studies in our country, by and large, focused on the impact of the disease in terms of mortality and morbidity alone. Therefore, the objective of this study was to assess the health-related quality of life (HRQOL) and associated factors of diabetic patients at the University of Gondar referral hospital, Ethiopia.

A facility-based cross-sectional study was conducted at the University of Gondar referral hospital from April to May 2017. A generic World Health Organization Quality of Life (WHOQOL-BREF) questionnaire was used to measure the HRQOL. The data were analyzed by Stata version 12. Multiple Linear Regression analysis with P -value 0.05 was used to measure the degree of association between HRQOL and independent variables.

A total of 408 patients with Diabetes Mellitus were included in the study. The HRQOL scores for physical, psychological, social and environmental domains were 50.9, 54.5, 55.8 and 47.3, respectively. Diabetes-related complications had a significant association with all except the psychological domain. Higher HRQOL was associated with exercising, following the recommended diet, foot care, sensible drinking and the absence of co-morbidities. However, old age, unemployment and being single and widower had a significant association with lower HRQOL.

The environmental and physical domains of HRQOL scores were the lowest compared to the social and psychological domains. Old age and living in rural area had a significant association with a lower HRQOL, whereas the absence of diabetes-related complications, exercising, general diet and foot care had a significant association with better HRQOL of patients. Therefore, strong advice on the recommended lifestyle is important, and old patients and rural dwellers should get due attention. In addition, the prevention of diabetes-related complications is important to improve the patient HRQOL which is an important outcome measurement from the patient’s perspective related to the impact of the disease. Therefore, including HRQOL assessment as part of routine management is necessary.

Diabetes mellitus (DM) is one of the chronic diseases that affect both developed and developing countries. The International Diabetics Federation (IDF) reported that in 2015, the disease affected 415 million people worldwide and will rise to 642 million in 2040. An estimated 14.2 million adults aged 20–79 suffer from diabetes in the Sub-saharan Africa. Ethiopia is one of the most populous countries in this region and has the highest number (1.3 million) of people with diabetes. The prevalence of DM, which is one of the four major chronic diseases in the country, is about 3.8% [ 1 , 2 ].

The impact of diabetes on a patient can be measured by traditional methods, like biochemical, morbidity and mortality although attention has recently been given to measuring health-related quality of life (HRQOL). HRQOL is important to assess the impact of the disease from the patient’s perspective [ 3 , 4 , 5 , 6 , 7 , 8 ]. Hence, HRQOL can be defined as “the subjective assessment of the impact of disease and its treatment across the physical, psychological and social domains of functioning and well-being” [ 9 ].

Diabetic patients feel about their blood glucose level and worry about the complications they might be developing or actually exist. Moreover, the never-ending care and lifestyle adjustments, like dietary change and exercise have an impact on patients’ HRQOL (physical, emotional and social well-being) [ 10 , 11 ]. Different studies have shown that the presence of diabetes has an impact on HRQOL and reduces the physical, psychological, environmental and social domains of health [ 12 , 13 , 14 , 15 ]. People with diabetes experience significant impairment in their HRQOL compared to non-diabetes people [ 16 , 17 , 18 ].

Health professionals can identify the physiological derangement and degree of deteriorations due to diabetes. Nevertheless, an individual patient’s health perceptions and well-being are not directly proportional to symptoms and functional limitations which in turn are not directly proportional to physiological and anatomic abnormalities. Therefore, the effects flowing from biological abnormalities to HRQOL are mediated and modified by psychological, social and cultural factors [ 19 ]. However, studies in our country, including those in the current study area focus on the impact of diabetes in terms of morbidity and mortality alone [ 20 , 21 , 22 ]. As far as we know, there has been no study on the psychosocial impact of diabetes in the study area. Therefore, this study aimed to determine the HRQOL of diabetic patients and to identify factors associated with it.

Study design and setting

An institution-based cross-sectional study was conducted at the University of Gondar referral hospital chronic illness follow-up outpatient clinic from April to May 2017 to assess HRQOL. The hospital, located in North Gondar zone, is one of the tertiary level health care facilities in Ethiopia. It has an outpatient department for chronic illness follow up and diabetes treatment provided 2 days a week to an average of 900 diabetic patients per month. It also has inpatient facilities where medical care is provided throughout the week.

Study population and sampling procedures

The population was all adult diabetic patients in the chronic illness follow up clinic during the study. All adult diabetic patients on follow-up for at least 6 months were included, whereas individuals with gestational diabetes and patients who were unable to communicate were excluded. The sample size was determined using a power approach (double population formula) from a previous study [ 23 ] by considering type I error of 0.05, type II error of 0.10, confidence interval 95%, standard deviation (SD) one 17.22, SD two 13.79, mean difference 5.2 and non-response 10%. Therefore, the final sample size of the study was 416. All diabetic patients who came to the University of Gondar referral hospital for follow ups were recruited consecutively until the minimum required sample size was reached.

Data collection tools and procedures

The World Health Organization quality of life (WHOQOL-BREF) the short version of the WHOQOL-100 SCALE was used to collect data. The questionnaire which contains 26 items was developed with 15 international field centers to obtain an assessment tool applicable cross-culturally [ 24 ]. The WHOQOL-BREF contains four specific domains (physical, psychological, social and environmental). The questionnaire was first adopted in the English language and translated to Amharic and back-translated to English to maintain its consistency. Factors relating to socio-demographics (age, sex, marital status, educational level, occupation, residence, ethnicity, religion and wealth index), clinical data (duration of diabetes, type of diabetes, diabetes-related complications, co-morbidities: any chronic diseases other than diabetes mellitus, body mass index, type of treatment and fasting blood glucose) and Lifestyle (smoking, physical exercise, diet, foot care and alcohol consumption) were included in the questionnaire.

Data on patient socio-demographics, lifestyle, HRQOL and some clinical data were collected by a trained interviewer, while some clinical data (co-morbidities, diabetes-related complications, diabetes type and fasting blood sugar) were taken from patients’ medical record cards.

Operational definitions

• Health-related quality of life

The instrument used was the WHOQOL-BREF of the WHOQOL-100 scale. This questionnaire contains 26 items computed into four specific domains: physical, psychological, social and environmental. The mean score on items within each domain was used to calculate the domains score. Higher scores denoted a higher HRQOL, and lower scores indicated lower HRQOL [ 24 ].

Body mass index

BMI was calculated by dividing weight into height squared and divided into four categories based on WHO classification [ 25 ]: underweight = < 18.5, normal weight = 18.5–24.9, overweight = 25–29.9 and obese = ≥30.

Alcohol consumption was assessed by using Fast alcohol screening test and split into two categories [ 26 ]: Non-hazardous drinker = < 3 and Hazardous drinker = ≥ 3.

Summary diabetes self-care activity (SDSCA)

This tool assessed the number of days per week on a scale of 0–7 on which the patient performed the recommended self-care activities [ 27 ].

General diet = Mean number of days the patient follows the recommended diet plan.

Specific diet = Mean number of days the patient eats fruits and fatty foods.

Exercise = Mean number of days the patient performs a minimum of 30 min activity.

Foot care = Mean number of days the patient takes care of their feet and check the inner part of their shoes.

Smoking status = (1 = smoker 2 = non-smoker).

Data analysis

The collected data were checked for completeness. Then, codes were given to each question and entered into Epi-Info Version 7 Software. Further analysis was done with Stata version 12. Where an item was missing, the mean of other items in the domain was substituted. But when more than two items were missing from the domain, the domain score was not calculated with the exception of domain 3, where the domain should be calculated if only one item is missing. Negatively framed questions (items 3, 4 and 26) were transformed into positively framed ones. Cronbach alpha was used to check the reliability of the items and domains. Raw and transformed scores were considered for the outcome variables. Summary statistics were done for the outcome and independent variables. Model assumptions (normality, equal variance, multicollinearity and linearity) were checked. Simple linear regression analysis was done to identify factors associated with each domain of HRQOL independently at a P -value < 0.2. Variables that were significant at a p -value of < 0.2 were selected for the final multiple linear regression model. In the multiple linear regression analysis, variables with P -values of < 0.05 were considered statistically significant.

Socio-demographic and economic characteristics of the study participants

A total of 416 diabetic patients participated in the study. Eight (1.92%) questionnaires were excluded from the analysis because they were incomplete. Of the participants, 54.7% were male, and 33.7% were unable to read and write. Their mean age (SD) was 47.48 ± 14.9 years (Table  1 ).

Clinical and lifestyle characteristics of study participants

Approximately, 56.6% of the participants were type 2 diabetes; 28.92% had co-morbidities, and 21.57% developed a diabetes-related complication (Table  2 ).

In this study, 41.91% of the participants rated their quality of life as good, and 18.14% were satisfied with their current health status (Table  3 ).

The four domains had good internal reliability with Cronbach Alpha: physical α = 0.77, psychological α = 0.69, social α = 0.73 and environmental α = 0.71. out of the 4 domains, the environmental domain HRQOL had the lowest mean score. In contrast, the social domain of HRQOL had the highest score (Table 4 ).

Factors associated with health-related quality of life

In this study, some socio-demographic, clinical and lifestyle variables were statistically significant determinants of each domain of HRQOL at a p -value of 0.05.

Age had a significant association (B = −.13, 95% CI = − 2.5, − 0.1), (B = −.16, 95% CI = −.30, −.01) and (B = −.20, 95% CI = −.34, −.05) with physical, psychological and social domains, respectively. Being single (B = − 6.70, 95% CI = − 12.43, −.97) and being widowed (B = − 6.64, 95% CI = − 12.6, -.613) had a significan association with the social and psychological domains, respectively. The environmental domain was significantly associated with secondary and above education level (B = 3.87, 95% CI = .14, 7.60), residence (B = − 3.88, 95% CI = − 7.72, −.04) and foot care (B = 1.12, 95% CI = .55, 1.70). Co-morbidity and occupation had a significant associate with physical domaim (B = 5.55, 95% CI = 2.55, 8.55). Diabetes-related complication statisticaly associated (B = 4.5, 95% CI = 1.17, 7.83), (B = 7.69, 95% CI = 3.18, 12.2) and (B = 3.88, 95% CI = .99, 6.77) with physical, social and environmental domains, respectively. Exercise was associated (B = 0.89, 95% CI = .08, 1.69) and (B = 1.28, 95% CI = .28, 2.29) with the physical and psychlogical domains, respectively. General diet had also a significant association (B = 0.84, 95% CI = 07, 1.61), (B = 1.14, 95% CI = .08, 2.20) and (B = 1.41, 95% CI = .71, 2.10) with the physical, psychlogical and environmental domains, respectively. Being hazardous drinker was statistically associate (B = 8.14, 95% CI = 4.08, 12.2) with the psychologicla domain (Table  5 ).

This study was done on patients with DM at the University of Gondar referral hospital. The results revealed that diabetes had an impact on HRQOL for diabetic patients in different domains. The maximum and minimum scores were related to social and environmental domains, respectively. Age, general diet and diabetes-related complications had a significant association with at least three domains of HRQOL.

The study found that patients had the lowest score (47.31 ± 2.51 out of 100) in the environmental domain compared to the three domains, whereas the social domain had the highest score (55.88 ± 17.63). The psychological and physical domains were also approximately average out of hundred. Although there was no cut-off point for WHOQOL-BREF to categorize HRQOL as high or low, the finding showed the score of each domain was approximately average and diabetes had an impact on patients’ health and well-being. Lifestyle modifications of diabetes treatment such, as diet (eating carefully), exercising, monitoring blood glucose, worry about complications associated with diabetes and the dependence of life (daily activity) on medication are some of the explanations for the reduction of HRQOL. These might cause negative feelings, such as depression, affect social interactions and recreational activities. Different studies have also shown that diabetes affects patient’s HRQOL compared to healthy individuals [ 28 , 29 ]. The result is in line with that of a study conducted in Kenya [ 12 ] in terms of the sequence of domains affected by diabetes.

In terms of all domains, the HRQOL score of this study is higher than that of Palestine, Gaza, which used similar tools [ 17 ]. The Possible explanation might be differences in psycho-social, cultural, economic, and environmental conditions. For instance, the participants of the present study lived in a stable and peaceful environment and had relatively their own living facility, access to the health facilities and other infrastructures compared to refugee patients in Gaza who depended on refugee camp supplies. Studies in Benin, Nigeria and Uganda [ 28 , 30 ] also have lower scores than the current study. A possible explanation might be differences in measurement tools.

A study in Iran with WHOQOL-BREF [ 23 ] shows the four domains of HRQOL are higher than those of the current study. A possible explanation might be differences in economic status, satisfaction with the infrastructure and health care service and clinical characteristics of patients. Moreover, studies from India also have higher scores than the current study [ 31 , 32 , 33 ].

Age had a significant association with all domains of HRQOL except the environmental domain. This is in line with those of studies in Kenya and Singapore [ 12 , 34 ]. This can be explained by the fact that age is related to several changes in the body and increases the risk of developing co-morbid diseases and further reduces individual well-being. The American Diabetes Association [ 35 ] also shows that the aging process leads to a degeneration of muscles, ligaments, bones, and joints and that diabetes may exacerbate the problem. Moreover, occupation and education had a significant association with the physical and environmental domains of HRQOL, respectively. Employed, farmer and retired had a higher score on the physical domain compared to unemployed. Patients with above secondary education level had a higher score on the environmental domain than those who were unable to read and write [ 13 , 30 , 36 ]. Education is an essential factor in understanding self-care management and perception of self-worth. The patients with a high educational level can easily read and understand the effects of diabetes and this might lead to better awareness about the disease such as complications. Furthermore, it contributes to a high rate of adherence to self-care management such as diet.

This study showed that patients without co-morbidities had a better score in the physical domains of HRQOL than patients with co-morbidities. This is supported by studies in Nigeria and Singapore [ 34 , 37 ]. Moreover, diabetic patients without diabetes-related complications had a better HRQOL in all domains except the psychological domain. This is in line with the findings of in Palestine and Singapore [ 17 , 34 ] that patients with diabetes-related complications had a lower HRQOL.

Marital status had a significant association with the social domain. Those who were single were more likely to have a lower HRQOL compared to the married ones. This is supported by a study in Nigeria, which reported that singles had lower odds of HRQOL than couples [ 38 ]. In addition, compared to married women widowed women had a lower score of the psychological domain of HRQOL. This might be because the probability of getting social or relative support is better for those who live in marital bonds.

Out of the lifestyle factors, exercise had a significant association with physical and psychological domains. Following a recommended general diet also had a significant association with all domains except the social domain. An interventional study in Sandiego, California [ 39 ], showed that exercising and adhering to the recommended diet had a positive impact on the HRQOL of patients. Studies in Nigeria and Canada [ 36 , 37 ] are also in line with this finding. As the number of days of foot care increased the psychological and environmental domains of HRQOL also improved. A study done in Uganda [ 30 ] revealed that patients with foot ulcers had a low HRQOL. Hence, foot care was a good measure to prevent foot ulcer and improve HRQOL by increasing patients’ sense of physical safety, enabling them to participate in recreation, and avoiding long-treatment, hospitalization and amputation. Finally, sensible drinkers had a better HRQOL of the psychological domain compared to the hazardous drinkers. Studies showed that moderate to heavy drinkers had a lower HRQOL (mental health) than nondrinkers or occasionally drinkers [ 40 , 41 ]. Alcohol consumption can impair an individual’s cognitive and altered consciousness. Studies revealed that alcohol consumption (excessive) impaired glycemic control which leads to worrying about the level of glucose, depression, complications and reduces satisfaction with their health status [ 42 ].

Compared to urban residents rural dwellers had a lower score in the environmental domain of HRQOL. Although evidence that directly compares residence with HRQOL is limited, there are clear differences with respect to access to health services, information, education and living standards between rural and urban settings. All these might contribute to the low score of the environmental domain of HRQOL. Studies, from the normal population, showed that subjects who live in the urban areas had a higher HRQOL than subjects who live in rural areas [ 43 , 44 ].

Limitation of the study

This was a cross-sectional study which was able only to detect associations, but not causalities. In addition, some important variables, like lipid profile and HgA1c were not included. As the study was conducted in one setting, findings might not be representative of the diabetic patients in other settings.

Diabetes has an impact on the patient’s HRQOL. The diabetic patients have often expressed their dissatisfaction with their health status and rated their quality of life as “poor” showed that the disease had a marked impact on their HRQOL. Environmental and physical domains of HRQOL were the lowest compared to the social and physical domains. Old age and living in rural areas had a significant association with low HRQOL, whereas the absence of diabetes-related complications, exercise, general diet and foot care were significantly associated with high HRQOL. Therefore, providing strong advice on the recommended lifestyle is important, and old age and rural dweller patients should get emphasis. In this respect, the prevention of diabetes-related complications is important to improve patient’s HRQOL which is an important outcome measurement from the patient’s perspective relating to the impact of the disease. Therefore, including HRQOL assessment as part of routine management is necessary. Since HRQOL is multidimensional, establishment of a multidisciplinary team of physicians, nutritionists, fitness coaches and social workers is important that works to educate and empower patients. Finally, a further longitudinal study will be needed for understanding the associations of factors influencing HRQOL.

Availability of data and materials

The datasets supporting the conclusions of this article are available upon request to the corresponding author. Due to data protection restrictions and participant confidentiality, we do not make participants’ data publicly available.

Abbreviations

Confidence interval

Diabetes Mellitus

Diabetes-related complication

International Diabetes Federation

Standard deviation

Summary of diabetes self-care activities

World Health Organization

World health organization quality of life bref

International Diabetes Federation. IDF Diabetes Atlas, 7th edn. Brussels, Belgium:. International Diabetes Federation. 2015.

Google Scholar  

Federal Democratic Republic of Ethiopia Ministry of Health. National Strategic Action Plan for Prevention and Control of Non Communicable Diseaes in Ethiopia, 2014–16. Ministry of Health.

Farquhar M. Definitions of quality of life: a taxonomy. J Adv Nurs. 1995;22(3):502–8.

Article   CAS   Google Scholar  

Karimi M, Brazier J. Health, health-related quality of life, and quality of life: what is the difference? PharmacoEconomics. 2016;34(7):645–9.

Article   Google Scholar  

Montori VM. Evidence-based endocrinology. Treat Endocrinol. 2004;3(1):1–10.

Verster JC, Pandi-Perumal SR, Streiner DL. Sleep and quality of life in clinical medicine: springer; 2008.

Book   Google Scholar  

Spertus J. Barriers to the use of patient-reported outcomes in clinical care. Circ Cardiovasc Qual Outcomes. 2014;7(1):2–4.

Sajid M, Tonsi A, Baig M. Health‐related quality of life measurement. International journal of health care quality assurance. 2008;21:365–73.

Revicki DA, Osoba D, Fairclough D, Barofsky I, Berzon R, Leidy N, et al. Recommendations on health-related quality of life research to support labeling and promotional claims in the United States. Qual Life Res. 2000;9(8):887–900.

Rubin RR. Diabetes and quality of life 2000 [Available from: http://journal.diabetes.org/diabetesspectrum/00v13n1/pg21.htm .

Healthcentral. How does diabetes impact lifestyle? 2017 [Available from: http://www.healthcentral.com/diabetes/patient-guide-44593-6.html .

Genga E, Otieno C, Ogola E, Maritim M. Assessment of the Perceived Quality of Life of Non insulin Dependent Diabetic patients attending the Diabetes Clinic in Kenyatta National Hospital. Diabetes Research and Clinical Practice; 2014: Elsevier IRELAND ltd ELSEVIER house, BROOKVALE plaza, east park SHANNON, co, CLARE, 00000, IRELAND.

Kakhki AD. Health-related quality of life of diabetic patients in Tehran. Int J Endocrinol Metabol. 2013;11(4):e7945.

Odili V, Ugboka L, Oparah A. Quality Of Life Of People With Diabetes In Benin City As Measured With WHOQOLBREF. Internet J Law Healthcare Ethics. 2008;6(2):1–7.

Spasić A, Radovanović RV, Đorđević AC, Stefanović N, Cvetković T. Quality of life in type 2 diabetic patients. Acta Facultatis Medicae Naissensis. 2014;31(3):193–200.

Morales M, Navas A, Jimenez M, Ramos J. Health-related quality of life in patients with type 2 diabetes mellitus in a rural area. J Diabetes Metab. 2015;6(572):1–5.

Eljedi A, Mikolajczyk RT, Kraemer A, Laaser U. Health-related quality of life in diabetic patients and controls without diabetes in refugee camps in the Gaza strip: a cross-sectional study. BMC Public Health. 2006;6(1):268.

Thommasen HV, Zhang W. Health-related quality of life and type 2 diabetes: a study of people living in the Bella Coola Valley. Br Columbia Med J. 2006;48(6):272.

Ormel J, Lindenberg S, Steverink N, Vonkorff M. Quality of life and social production functions: a framework for understanding health effects. Soc Sci Med. 1997;45(7):1051–63.

Abebe SM, Berhane Y, Worku A, Assefa A. Diabetes mellitus in north West Ethiopia: a community based study. BMC Public Health. 2014;14(1):97.

Alemu F. Prevalence of diabetes mellitus disease and its association with level of education among adult patients attending at Dilla Referral Hospital, Ethiopia. J Diabetes Metabol. 2015;6(4):1–5.

Habtewold TD, Tsega WD, Wale BY. Diabetes mellitus in outpatients in Debre Berhan referral hospital, Ethiopia. J Diabetes Res. 2016;2016:1–6.

Tavakkoli L, Dehghan A. Compare the Quality of Life in Type 2 Diabetic Patients with Healthy Individuals (Application of WHOQOL-BREF). Zahedan J Res Med Sci. 2017;19(2):1–6.

World Health Organization. WHOQOL-BREF: introduction, administration, scoring and generic version of the assessment: field trial version, December 1996. 1996.

Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr. 2000;72(3):694–701.

Dr Tina Alwyn DBJ, Dr Alyson Smith Fast screening for alcohol problems: manual for the fast alcohol screening test. Available from:  http://www.dldocs.stir.ac.uk/documents/fastmanual.pdf . Accessed Mar 20 2017.

Glasgow RE, Barrera M Jr, Mckay HG, Boles SM. Social support, self-management, and quality of life among participants in an internet-based diabetes support program: a multi-dimensional investigation. CyberPsychol Behav. 1999;2(4):271–81.

Odili V, Ugboka L, Oparah A. Quality of life of people with diabetes in Benin City as measured with WHOQOL-BREF. Int J Law Health Ethics. 2008;6(2):1–7.

Živčicová E, Gullerová M. Quality of Life Comparison of People with and without Diabetes Mellitus. CBU International Conference Proceedings; 2015.

Nyanzi R, Wamala R, Atuhaire LK. Diabetes and quality of life: a Ugandan perspective. J Diabetes Res. 2014;2014:402012.

Gautam Y, Sharma A, Agarwal A, Bhatnagar M, Trehan RR. A cross-sectional study of QOL of diabetic patients at tertiary care hospitals in Delhi. Indian J Community Med. 2009;34(4):346.

Khongsdir S, George C, Mukherjee D, Norman G. Quality of life in patients with diabetes and hypertension in Karnataka-an observational study. Int J Med Health Sci. 2015;4(1):98–102.

Somappa HK, Venkatesha M, Prasad R. Quality of life assessment among type 2 diabetic patients in rural tertiary Centre. Int J Med Sci Public Health. 2014;3(4):415–7.

Quah JH, Luo N, Ng WY, How CH, Tay EG. Health-related quality of life is associated with diabetic complications, but not with short-term diabetic control in primary care. Ann Acad Med Singapore. 2011;40(6):276.

PubMed   Google Scholar  

American Diabetic Association. American Diabetes Association Standards of Medical Care in Diabetes 2017 [Available from: https://professional.diabetes.org/files/media/dc_40_s1_final.pdf .

Imayama I, Plotnikoff RC, Courneya KS, Johnson JA. Determinants of quality of life in type 2 diabetes population: the inclusion of personality. Qual Life Res. 2011;20(4):551–8.

Adeniyi A, Ogwumike O, Oguntola D, Adeleye J. Interrelationship among physical activity, quality of life, clinical and sociodemographic characteristics in a sample of Nigerian patients with type 2 diabetes. Afr J Physiother Rehabil Sci. 2015;7(1–2):12–8.

Issa B, Baiyewu O. Quality of life of patients with diabetes mellitus in a Nigerian teaching hospital. Hong Kong J Psychiatry. 2006;16(1):27.

Kaplan RM, Hartwell SL, Wilson DK, Wallace JP. Effects of diet and exercise interventions on control and quality of life in non-insulin-dependent diabetes mellitus. J Gen Intern Med. 1987;2(4):220–8.

Daeppen J-B, Faouzi M, Sanchez N, Rahhali N, Bineau S, Bertholet N. Quality of life depends on the drinking pattern in alcohol-dependent patients. Alcohol Alcohol. 2014;49(4):457–65.

Ortolá R, García-Esquinas E, Galán I, Rodríguez-Artalejo F. Patterns of alcohol consumption and health-related quality of life in older adults. Drug Alcohol Depend. 2016;159:166–73.

Engler PA, Ramsey SE, Smith RJ. Alcohol use of diabetes patients: the need for assessment and intervention. Acta Diabetol. 2013;50(2):93–9.

Oguzturk O. Differences in quality of life in rural and urban populations. Clin Invest Med. 2008;31(6):E346–E50.

Weeks WB, Kazis LE, Shen Y, Cong Z, Ren XS, Miller D, et al. Differences in health-related quality of life in rural and urban veterans. Am J Public Health. 2004;94(10):1762–7.

Download references

Acknowledgments

We are very thankful to the University of Gondar for the approval of the ethical issue and its technical and financial support. We forward our appreciation to the hospital managers for allowing us to conduct this research and their cooperation. Finally, we would like to thanks study participants for their volunteer participation and also data collectors and supervisors for their genuineness and quality of work during data collection.

This is part of a master thesis funded by the University of Gondar. The preliminary findings of this study were presented at the Institute of Public Health, University of Gondar. After incorporating the comments, the authors have prepared this manuscript for publication at BMC Health and Quality of Life Outcomes. The funders had no role in the study design, data collection, analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and affiliations.

Department of Health Systems and Policy, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia

Andualem Yalew Aschalew, Mezgebu Yitayal & Amare Minyihun

You can also search for this author in PubMed   Google Scholar

Contributions

AY designed the study, developed data collection tools, performed the analysis and interpretation of data and drafted the paper. MY and AM participated in the development of the study proposal, analysis and interpretation, revised drafts of the paper, revised the manuscript. All authors read and approved the final manuscript.

Authors’ information

AY is a lecturer of Health Economics in the Department of Health Systems and Policy, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

MY is an Associate Professor of Health Service Management and Health Economics in the Department of Health Systems and Policy, Institute of Public Health; and a member of a research team in the Dabat Health and Demographic Surveillance System, University of Gondar, Gondar, Ethiopia.

AM is a Lecturer of Health Economics in the Department of Health Systems and Policy, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Corresponding author

Correspondence to Andualem Yalew Aschalew .

Ethics declarations

Ethics approval and consent to participate.

The study was conducted after ethical approval was obtained from the Ethical Review Board of the Institute of Public Health, College of Medicine and Health Science, University of Gondar (Ref. No.: IPH/2429/2017). Permission letters were obtained from the University of Gondar Referral Hospital. All study participants were oriented on the objectives and purpose of the study prior to study participation. Confidentiality and anonymity were explained. Patients at health facilities and sick individuals were informed that participation had no impact on the provision of their health care. Study team members safeguarded the confidentiality and anonymity of study participants throughout the entire study. Interviews were conducted in quiet areas, enclosed whenever possible, to ensure participant privacy. In order to protect the identities of the study participants, each participant was given a unique identification number (ID). All forms and data related to the study were stored in a locked room in a secured area, with controlled access available only to the investigator and supervisors. Participation in the study was voluntary and individuals were free to withdraw or stop the interview at any time.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Aschalew, A.Y., Yitayal, M. & Minyihun, A. Health-related quality of life and associated factors among patients with diabetes mellitus at the University of Gondar referral hospital. Health Qual Life Outcomes 18 , 62 (2020). https://doi.org/10.1186/s12955-020-01311-5

Download citation

Received : 19 February 2019

Accepted : 02 March 2020

Published : 10 March 2020

DOI : https://doi.org/10.1186/s12955-020-01311-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Diabetes mellitus
• WHOQOL-BREF

Health and Quality of Life Outcomes

ISSN: 1477-7525

• Submission enquiries: [email protected]

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 09 May 2024

Prevalence and factors associated with diabetes-related distress in type 2 diabetes patients: a study in Hong Kong primary care setting

• Man Ho Wong 1 ,
• Sin Man Kwan 1 ,
• Man Chi Dao 1 ,
• Sau Nga Fu 1 &
• Wan Luk 1  

Scientific Reports volume  14 , Article number:  10688 ( 2024 ) Cite this article

331 Accesses

1 Altmetric

Metrics details

• Endocrine system and metabolic diseases

Diabetes-related distress (DRD) refers to the psychological distress specific to living with diabetes. DRD can lead to negative clinical consequences such as poor self-management. By knowing the local prevalence and severity of DRD, primary care teams can improve the DRD evaluation in our daily practice. This was a cross-sectional study conducted in 3 General Out-patient Clinics (GOPCs) from 1 December 2021 to 31 May 2022. A random sample of adult Chinese subjects with T2DM, who regularly followed up in the selected clinic in the past 12 months, were included. DRD was measured by the validated 15-item Chinese version of the Diabetes Distress Scale (CDDS-15). An overall mean score ≥ 2.0 was considered clinically significant. The association of DRD with selected clinical and personal factors was investigated. The study recruited 362 subjects (mean age 64.2 years old, S.D. 9.5) with a variable duration of living with T2DM (median duration 7.0 years, IQR 10.0). The response rate was 90.6%. The median HbA1c was 6.9% (IQR 0.9). More than half (59.4%) of the subjects reported a clinically significant DRD. Younger subjects were more likely to have DRD (odds ratio of 0.965, 95% CI 0.937–0.994, p  = 0.017). Patients with T2DM in GOPCs commonly experience clinically significant DRD, particularly in the younger age group. The primary care clinicians could consider integrating the evaluation of DRD as a part of comprehensive diabetes care.

Similar content being viewed by others

Prevalence and predictors of diabetes-related distress in adults with type 1 diabetes

Psychometric validation of diabetes distress scale in Bangladeshi population

Impact of diabetes distress on glycemic control and diabetic complications in type 2 diabetes mellitus

Introduction.

It is estimated that the prevalence of type 2 diabetes mellitus (T2DM) in adults in Hong Kong (HK) is approximately 10% of the population 1 . The Hospital Authority of Hong Kong provides public healthcare services to around 400,000 diabetic patients, with the General Out-patient Clinics (GOPCs) offering primary care to over 60% of these individuals 2 . People living with T2DM are affected by this chronic and progressive condition not only physically, but also emotionally. Diabetes-related distress (DRD) refers to the psychological distress specific to living with diabetes. It includes a wide range of emotions, such as feeling overwhelmed by the demands of self-management and restrictions. People with T2DM have to control diet, regularly do exercise and take medications 3 . Many of them may have fears of existing or future diabetes complications, concerns about hypoglycaemia and frustration with care providers 4 .

DRD involves emotional symptoms that may overlap with some psychological conditions, such as depression. However, a previous literature has demonstrated that DRD and depression are different constructs that need different assessment and management approaches 5 . Compared to depression, DRD is peculiar to the emotional distress caused by relentless self-management of diabetes and it does not imply underlying psychopathology. Also, DRD is more closely associated with diabetes-related behavioural and biomedical outcomes than depression. Particularly, it has been shown that DRD influences glycaemic control whereas the impact of depression appears to be equivocal 5 , 6 , 7 . Compared to depression, DRD is highly responsive to clinical intervention 4 . A systemic review has shown that interventions delivered by primary care clinicians, psychoeducation and motivational interviewing resulted in significant DRD reduction 8 .

DRD is prevalent among patients with T2DM, in which a meta-analysis demonstrated the overall prevalence of DRD was 36% 2 . Also, studies in China found that 42.5–77.2% of Chinese people with T2DM experienced DRD 9 , 10 , 11 , 12 . The occurrence of DRD may be influenced by age, gender, culture, type of diabetes, use of insulin, number of complications and duration of diabetes 13 . DRD can lead to negative clinical consequences as studies have shown that a high level of DRD was associated with poor self-management, suboptimal glycaemic control and poor quality of life 14 , 15 , 16 , 17 . The American Diabetes Association recommended that DRD should be routinely monitored, particularly when treatment targets are not met and/or at the onset of diabetes complications 18 . However, DRD is not assessed or recognized in most of the primary care practices in Hong Kong. Since the local prevalence and severity of DRD remain unknown, it is difficult to determine whether DRD assessment should be routinely included in local DM care.

The primary objective of this study was to study the proportion of clinically significant DRD among patients with T2DM in GOPCs in HK. The secondary objective was to identify the associated factors of DRD.

There are 2 hypotheses in this study. (1) The proportion of clinically significant DRD among patients with T2DM in GOPC in HK is common, which is at least 36%, according to existing literature. (2) There is a significant association of DRD with demographic and clinical parameters.

Methodology

Study design.

This was a cross-sectional and prospective study conducted in three GOPCs in HK from 1 December 2021 to 31 May 2022. The three GOPCs include South Kwai Chung Jockey Club GOPC, Ha Kwai Chung GOPC and Cheung Sha Wan Jockey Club GOPC. The inclusion criteria were all adult Chinese patients, who had known diagnosis of T2DM and had at least two regular follow-ups for T2DM in the selected clinic in the past 12 months.

The exclusion criteria were patients diagnosed with type 1 diabetes, patients who had active follow-up of T2DM or were prescribed DM medications in Medicine Department specialist out-patient clinic, patients with known psychiatric illnesses who had active follow-up in either Psychiatry specialists or mental health services, patients who did not have diabetes related blood tests in the past 12 months from the study period, pregnant women, patients who did not understand written Chinese and mentally incapacitated persons.

A list of patients assigned with the International Classification of Primary Care (ICPC) code T90 (Diabetes; non-insulin-dependent) in the selected clinic was drawn from the Hospital Authority’s Clinical Data Analysis and Reporting System (CDARS) 2 weeks prior to the scheduled follow-up appointment with a corresponding appointment number. Up to 5 patients were selected from the list using random number table each day during the study period. A reminder was set in the computer system to identify those selected patients. The patients were invited and asked for consent to participate the study by the attending doctors. Information sheets about the study were given. Patients would complete the questionnaire individually and return it to the healthcare assistant in the clinic. Patients who refused to participate or give consent in this study were regarded as non-responders. Patients who had incomplete questionnaires or missing data were excluded from the statistical analysis. This study follows the principles of Declaration of Helsinki.

Sample size

The sample size was calculated by using the sample size formula:

where the desired precision was taken to be within 5% at 95% confidence interval.

Z = value from standard normal distribution corresponding to desired confidence level (Z = 1.96 for 95% CI)

P is expected true proportion

e is desired precision (margin of error).

The expected proportion in the study population was set to be 36% based on the overall prevalence in the previous meta-analysis study 2 .

Assuming the response rate was 90%, the sample size was estimated to be 355/0.9 = 395 patients, which would round up to 400 patients. Thus, we would aim at recruiting at least 400 patients.

Measurement

Diabetes Distress Scale (DDS) is one of the most commonly used and validated self-report measures to evaluate DRD internationally. The DDS is specific to patients with T2DM and provides a more comprehensive assessment to overcome the psychometric limitations of other measures such as Problems Areas in Diabetes (PAID) scale 2 . Another strength is that DDS also allows healthcare providers to identify the key sources of DRD 4 . The Chinese version of the Diabetes Distress Scale (CDDS-15) was validated in Hong Kong with consistent factor structure and good internal reliability (Cronbach’s alpha 0.902), which is specific for clinical use in Hong Kong Chinese type 2 diabetic patients 19 . There are 3 categories of CDDS-15, consisting of emotional burden (6 items), regimen- and social support- related distress (6 items), and physician-related distress (3 items) 19 . Each item was rated by patients using a 6-point Likert scale from 1 for “not a problem” to 6 for “a very serious problem.” The total mean item score was determined by adding the responses for all items and dividing by 15. Each subscale mean score was calculated by summing item responses in that subscale and dividing by the corresponding number of items. As reported by the study “When is diabetes distress clinically meaningful?: establishing cut points for the Diabetes Distress Scale”, an overall mean score ≥ 2.0 is considered clinically significant 17 . DRD was regarded as a dichotomous variable in this study, with subjects considered to have clinically significant DRD if CDDS-15 mean score ≥ 2.0.

We collected the data by using a printout questionnaire, consisting of three components: (1) The score of the CDDS-15; (2) demographic characteristics such as age, gender, education level, employment status, need of financial assistance to support basic living with Comprehensive Social Security Assistance (CSSA), living arrangement, and smoking status; (3) clinical parameters were obtained by reviewing participants’ medical records, including duration of T2DM, number of oral hypoglycaemic agent, use of insulin, latest Haemoglobin A1c (HbA1c) level, body mass index (BMI), diabetes complications and frequency of hypoglycaemic episodes in the past month. (see Appendix).

The primary outcome was the proportion of DRD among patients with T2DM in the selected study centres. The secondary outcome was the associated factors of DRD including demographic characteristics and clinical parameters as mentioned above.

Statistical analysis

The collected data was analyzed using the IBM Statistical Product and Service Solutions (SPSS) version 25 software. Qualitative variables were presented as frequencies and percentages. Quantitative variables were described as mean and standard deviation (SD), or median and interquartile range (IQR), as appropriate.

Pearson’s Chi-squared test was performed to compare the qualitative variables between participants without clinically significant DRD (DDS < 2) and participants with clinically significant DRD (DDS ≥ 2). Student’s t- test and Mann–Whitney U test was applied for quantitative variables with normal and non-normal distribution, respectively. When variables showed a p -value < 0.2 in the univariate analysis, they would be incorporated into the multivariate analysis. It was done to assure that all potentially associated variables were studied. Logistic regression analysis was used to adjust the confounding effect between variables and to identify the associated factors of DRD in those participants. Findings were considered statistically significant when the p -value < 0.05.

Ethics approval and consent to participate

Informed consent in written form was obtained from all patients. The study was approved by the Hospital Authority Kowloon West Cluster Research Ethics Committee (KWC REC Reference: KW/EX-21-121(162-06)). The CDDS-15 questionnaire was granted permission for use in this study by American Diabetes Association (Permission Request Number: KL072021-MHW). This study follows the principles of Declaration of Helsinki.

Patients’ demographic and clinical characteristics

We distributed 408 questionnaires, thirty-eight patients refused to participate in the study and the response rate was 90.6%. Eight questionnaires were found to have incomplete data and were discarded. Therefore, the total number of questionnaires included in the statistical analysis was 362.

Among the 362 participants, the mean age was 64.2 years old (SD 9.5) and male to female ratio was approximately 1:1. Fewer than 8% of participants (n = 27) had attained tertiary education. Approximately 40% of the participants (n = 146) were retired. The median HbA1c was 6.9% (IQR 0.9). The median duration of living with T2DM since diagnosis was 7.0 years (IQR 10.0). The mean BMI was 26.0 (SD 3.9). For the regimen type, approximately 90% of the participants (n = 324) were taking oral hypoglycaemic agents with or without insulin. The participants’ demographic and clinical characteristics were presented in Table 1 .

Proportion of DRD

A total of 59.4% of the study participants were found to have clinically significant DRD according to the total mean item score (DDS ≥ 2). Among the 3 subscales of DRD, emotional burden was observed in 64.9% of participants, followed by regimen- and social support-related distress (64.1%). Physician-related distress (33.7%) was relatively less affected. This is illustrated in Fig.  1 .

The proportion of clinically significant DRD among patients with T2DM in different subscales (n = 362).

Factors associated with DRD

In the univariate analysis, age and employment status were found to be significantly associated with DRD (unadjusted p  < 0.05). These factors, together with other variables with unadjusted p  < 0.2 including BMI, HbA1c level and regimen type, were further analyzed in the multivariate logistic regression, as shown in Table 2 . Only age was significantly associated with the occurrence of DRD among patients with T2DM, in which the adjusted odds ratio was 0.965 (95% CI 0.937–0.994, adjusted p  = 0.017).

In our study, 59.4% of patients with T2DM in the GOPC setting in HK suffered from clinically significant DRD. It is comparable to the studies in China with a reported prevalence 42.5–77.2% 9 , 10 , 11 , 12 . However, it is much higher than the overall prevalence 36% in the meta-analysis, in which the majority of the studies involved were from Western countries 2 . In Asia, the prevalence of DRD was reported to be 32%, 49%, and 53% in Singapore, Malaysia, and India, respectively 20 , 21 , 22 . The prevalence varies substantially across countries. This could be explained by the difference in the healthcare system, demographics, and cultural background.

Among the 3 subscales of DRD, the proportion of physician-related distress was the lowest in this study, which is similar to the findings in other studies 17 , 23 . Participants might not attribute their distress to physicians if they could obtain sufficient expertise and direction from physicians regarding their T2DM management. Nonetheless, healthcare professionals should pay more attention to the emotional side of diabetes care as more than 60% of subjects in this study had clinically significant emotional burden and regimen- and social support-related distress.

Our study showed that older age was associated with lower odds of DRD (OR 0.965). This is consistent with the results of other studies 24 , 25 , 26 . One study showed that the relation of DRD to psychological and behavioral outcomes is attenuated in older adults, regardless of the duration of T2DM 27 . One hypothesis is that older adults react less to stress because their previous experiences in coping with stress have led to better emotion regulation strategies 28 . On the other hand, younger patients usually have more responsibilities at work and family such as supporting their children and elderly family members 26 . These stressors can worsen the burden associated with the self-management of T2DM.

The HbA1c level was not significantly associated with DRD in our study. This is in line with the results of various international studies 2 , 16 , 23 . In contrast, a study conducted in a specialist clinic in HK using the CDDS-15 questionnaire showed that DRD had a positive relationship with HbA1c level 29 . The disparity may be explained by the difference in the healthcare setting and patients’ demographics. Also, only a minority of patients (7.5%) were prescribed insulin in the GOPC setting in our study, whereas 48% of the subjects were prescribed insulin in the specialist clinic in that study. In fact, there is mixed evidence in the literature regarding the relationship between glycaemic control and DRD 4 . Although DRD is modestly associated with poor glycaemic control, patients with good glycaemic control can also experience high DRD 4 , 16 . Achieving the HbA1c target may require intensive efforts that are potentially impacting other areas of their life such as social activities. This implies patients with T2DM may have an ongoing fear of disease complications or encounter challenges of self-management regardless of their latest glycaemic control.

The strengths of this study were that it was a multi-center study and there was a relatively high response rate. Measures such as invitations by healthcare providers could help reduce the number of non-responders. Moreover, it was one of the pioneer studies regarding DRD in the primary care setting in HK.

However, there are several limitations of this study. First, the use of a self-reported instrument in this study was influenced by social desirability bias. Physician-related distress might be underestimated in this study as patients might worry about negative effects on their treatment process if they declare a lack of confidence in the physician’s expertise in their diabetes management 30 . Second, the causality of the relationships could not be determined due to the study’s cross-sectional design. Further longitudinal studies are suggested to delineate causal relationships. Third, this study was conducted in three GOPCs only and there could be selection bias, therefore the study findings cannot be generalized to all patients with T2DM in HK. Fourth, it is important to acknowledge the restricted scope of this study on assessing other comorbidities such as hypertension and hyperlipidaemia. This study focused primarily on the clinical conditions directly associated with diabetes, including macrovascular and microvascular complications. Future studies could consider incorporating a boarder range of comorbidities to gain a more comprehensive understanding of the impact of diabetes-related distress. Lastly, as the study period coincided with the fifth wave of COVID-19 in HK, it could be a particularly stressful time for patients with T2DM to comply with their diet plan and exercise routine.

There are some clinical implications drawn from this study. Family physicians are on the frontlines responsible for the diagnosis and management of patients with T2DM and this study showed that a high proportion of patients with T2DM experience psychological distress. This finding alerts family physicians about the importance of a holistic approach in T2DM management. Regular evaluation of DRD by a self-reported instrument could be considered to incorporate with the annual assessment of T2DM in the GOPC setting. DRD does not typically disappear when left unaddressed, but DRD interventions do not require the expertise of a mental health professional 4 . In most cases, interventions offered by family physicians including motivational interviewing can help relieve DRD and thus improve the self-management of T2DM 4 , 8 . A practical guide on addressing DRD in clinical care is also available 4 . Further research on monitoring and addressing DRD in primary care in HK is warranted.

The psychological component of diabetes is not routinely assessed in most of the primary care practices in HK. This study demonstrated that a high proportion of patients with T2DM in GOPCs experience clinically significant DRD. Younger age was identified as an associated factor. Evaluation of DRD is suggested to integrate as a part of comprehensive diabetes care in the primary care setting.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Quan, J. et al. Diabetes incidence and prevalence in Hong Kong, China during 2006–2014. Diabet Med. 34 , 902–908 (2017).

Article   CAS   PubMed   Google Scholar  

Lau, I. T. A clinical practice guideline to guide a system approach to diabetes care in Hong Kong. Diabetes Metab J. 41 (2), 81–88 (2017).

Article   PubMed   PubMed Central   Google Scholar  

Perrin, N. E. et al. The prevalence of diabetes-specific emotional distress in people with Type 2 diabetes: A systematic review and meta-analysis. Diabet. Med. 34 (11), 1508–1520 (2017).

Fisher, L., Polonsky, W. H. & Hessler, D. Addressing diabetes distress in clinical care: A practical guide. Diabet. Med. 36 (7), 803–812 (2019).

Fisher, L. et al. Diabetes distress but not clinical depression or depressive symptoms is associated with glycemic control in both cross-sectional and longitudinal analyses. Diabetes Care 33 (1), 23–28 (2010).

Article   PubMed   Google Scholar  

Adriaanse, M. C. et al. Diabetes-related symptom distress in association with glucose metabolism and comorbidity: The Hoorn Study. Diabetes Care 31 (12), 2268–2270 (2008).

Van Bastelaar, K. M. et al. Diabetes-specific emotional distress mediates the association between depressive symptoms and glycaemic control in Type 1 and Type 2 diabetes. Diabet. Med. 27 (7), 798–803 (2010).

Sturt, J. et al. Effective interventions for reducing diabetes distress: Systematic review and meta-analysis. Int. Diabetes Nurs. 12 (2), 40–55 (2015).

Article   Google Scholar  

Jianbin, L. & Yanjun, Y. Study on the relationship between quality of life and diabetic distress in type 2 diabetes patients in Guangzhou. J. Trop. Med. 19 (3), 369–372 (2019).

Google Scholar  

Bao, H., Liu, J. & Ye, J. Influencing factors of the diabetes distress among Chinese patients with type 2 diabetes mellitus. Psychiat. Danubina 30 (4), 459–465 (2018).

Article   CAS   Google Scholar  

Zhang, J. et al. Comparative study of the influence of diabetes distress and depression on treatment adherence in Chinese patients with type 2 diabetes: A cross-sectional survey in the People’s Republic of China. Neuropsychiatr. Dis. Treat. 9 , 1289–1294 (2013).

PubMed   PubMed Central   Google Scholar  

Zhou, H. et al. Diabetes-related distress and its associated factors among patients with type 2 diabetes mellitus in China. Psychiatry Res. 252 (6), 45–50 (2017).

Stoop, C. H. et al. Diabetes-specific emotional distress in people with Type 2 diabetes: A comparison between primary and secondary care. Diabet Med. 31 (10), 1252–1259 (2014).

American Diabetes Association. Standards of medical care in diabetes-2014. Diabetes Care 37 (suppl), S14–S80 (2014).

Aikens, J. E. Prospective associations between emotional distress and poor outcomes in type 2 diabetes. Diabetes Care. 35 (12), 2472–2478 (2012).

Fisher, L. et al. Predicting diabetes distress in patients with Type 2 diabetes: A longitudinal study. Diabet. Med. 26 (6), 622–627 (2009).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Fisher, L. et al. When is diabetes distress clinically meaningful?: Establishing cut points for the Diabetes Distress Scale. Diabetes Care. 35 (2), 259–264 (2012).

American Diabetes Association. Standards of medical care in diabetes-2022 abridged for primary care providers. Clin. Diabetes. 40 (1), 10–38 (2022).

Article   PubMed Central   Google Scholar  

Ting, R. Z. et al. Diabetes-related distress and physical and psychological health in Chinese type 2 diabetic patients. Diabet. Care. 34 , 1094–1096 (2011).

Venkataraman, K. et al. Properties of the problem areas in diabetes (PAID) instrument in Singapore. PLoS One 10 (9), e0136759 (2015).

Chew, B. H. et al. Diabetes-related distress, depression and distress-depression among adults with type 2 diabetes mellitus in Malaysia. PLoS One. 11 (3), e0152095 (2016).

Sasi, S. T. et al. Self Care activities, diabetic distress and other factors which affected the glycaemic control in a tertiary care teaching hospital in South India. J. Clin. Diagn. Res. 7 (5), 857–860 (2013).

Kamrul-Hasan, A. B. M. et al. Prevalence and predictors of diabetes distress among adults with type 2 diabetes mellitus: A facility-based cross-sectional study of Bangladesh. BMC Endocr. Disord. 22 (1), 28 (2022).

Hessler, D. M. et al. Patient age: A neglected factor when considering disease management in adults with type 2 diabetes. Patient Educ. Couns. 85 (2), 154–159 (2011).

Polonsky, W. H. et al. Assessing psychosocial distress in diabetes: Development of the diabetes distress scale. Diabetes Care. 28 (3), 626–631 (2005).

Hu, Y., Li, L. & Zhang, J. Diabetes distress in young adults with type 2 diabetes: A cross-sectional survey in China. J. Diabetes Res. 18 (2020), 4814378 (2020).

Helgeson, V. S., Van Vleet, M. & Zajdel, M. Diabetes stress and health: Is aging a strength or a vulnerability?. J. Behav. Med. 43 (3), 426–436 (2020).

Berg, C. A. & Upchurch, R. A developmental-contextual model of couples coping with chronic illness across the adult life span. Psychol. Bull. 133 (6), 920–954 (2007).

Lau, C. Y. K. et al. Coping skills and glycaemic control: The mediating role of diabetes distress. Acta Diabetol. 58 (8), 1071–1079 (2021).

Khashayar, P. et al. Diabetes-related distress and its association with the complications of diabetes in Iran. J. Diabetes Metab. Disord. 27 , 1–7 (2022).

Download references

Acknowledgements

I would like to thank American Diabetes Association for granting us permission to use the CDDS-15 questionnaire in our study. In addition, I would like to thank all the doctors, nurses and staff for supporting this study.

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

Author information

Authors and affiliations.

Family Medicine and Primary Health Care Department, Kowloon West Cluster, Hospital Authority, Kowloon, Hong Kong

Man Ho Wong, Sin Man Kwan, Man Chi Dao, Sau Nga Fu & Wan Luk

You can also search for this author in PubMed   Google Scholar

Contributions

All authors contributed to the concept or design of the study, acquisition of data, analysis or interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content. All authors had full access to the data, contributed to the study, approved the final version for publication, and take responsibility for its accuracy and integrity.

Corresponding author

Correspondence to Man Ho Wong .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary information., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Wong, M.H., Kwan, S.M., Dao, M.C. et al. Prevalence and factors associated with diabetes-related distress in type 2 diabetes patients: a study in Hong Kong primary care setting. Sci Rep 14 , 10688 (2024). https://doi.org/10.1038/s41598-024-61538-w

Download citation

Received : 10 October 2023

Accepted : 07 May 2024

Published : 09 May 2024

DOI : https://doi.org/10.1038/s41598-024-61538-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Type 2 diabetes
• Diabetes-related distress
• Emotional burden
• Chinese version of the diabetes distress scale (CDDS-15)
• Diabetes care

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• v.15(4); 2023 Apr
• PMC10230119

Knowledge and Awareness About Diabetes Mellitus Among Urban and Rural Population Attending a Tertiary Care Hospital in Haryana

Dr.lalit kumar.

1 Internal Medicine, Adesh Medical College and Hospital, Shahbad, Kurukshetra, IND

Rahul Mittal

Akhil bhalla.

2 Pain Medicine, Adesh Medical College and Hospital, Shahbad, Kurukshetra, IND

Ashwani Kumar

Hritik madan, kushagra pandhi.

3 Pharmacy, Adesh Institute of Pharmacy and Biomedical Sciences, Adesh University, Bathinda, IND

Kamaldeep Singh

4 Internal Medicine, Jawaharlal Nehru Medical College, Chandigarh, IND

5 Emergency Medicine, All India Institute of Medical Sciences, New Delhi, New Delhi, IND

Background: Diabetes mellitus (DM) is one of the fastest-growing public health problems in the twenty-first century. The ignorance among people about their disease may be related to their low socioeconomic status and lack of quality education available to them about the disease. It is a serious condition leading to several complications if the individual does not follow up regularly for check-ups and blood sugar monitoring. Lifestyle modifications such as a healthy diet, regular exercise, reducing weight, stress management, and smoking cessation can play a critical role in managing diabetes and improving the health and well-being of diabetic patients. Thus, through this study, we want to assess and create awareness among diabetic patients.

Methodology: It is a hospital-based cross-sectional study conducted at a tertiary care hospital on diagnosed cases of DM. The patients aged 18 years or above of either gender who had already been diagnosed with DM type 1 and type 2 were included, and patients with gestational DM were excluded from the study. Informed consent was taken from the patients, and all the required details were obtained using a well-structured questionnaire. After obtaining all the answers, the level of knowledge and awareness was analyzed, and the data was entered into an MS Excel sheet (Microsoft, Redmond, Washington) and analyzed by Statistical Package for the Social Sciences (SPSS) version 22.0 (IBM Corp., Armonk, NY).

Results: In our study, the maximum prevalence of diabetes was seen in males (55.5%) than females (44.5%), and the mean age of our study population was 53.3 ± 16.4 years. In our study, participants from rural areas made up the majority (59%) compared to those from urban areas (41%), and the majority of participants had a high school education. Among 211 diabetics, about 84%, 79%, and 41% of the patients knew about diabetes, symptoms of diabetes, and complication of diabetes. Only 18% of the patients were aware of the symptoms of hypoglycemia, and 38% of the patients possess their own glucometers and monitor their blood sugar levels on a regular basis. Merely 38% of the diabetics were aware of the various DM treatment choices. About 52% of patients had some awareness of insulin therapy. Out of 211 patients, about half skipped their antidiabetic prescriptions, and of those, 22% took a double dose the next day. A total of 121 patients (57%) combined the use of alternative and allopathic medications, and among these, 22% of patients had replaced the allopathic with alternative medicines. Almost 53% of patients had a positive family history of diabetes; 54% of patients believe that obesity is unrelated to diabetes, and 79% of diabetics are aware of the lifestyle changes that must be done for diabetes. Almost 67% of the patients believed that diabetes could be permanently treated, and 84% of patients believed that eating too much sugar caused their diabetes.

Conclusion: In our study, a significant number of patients suffering from diabetes had less knowledge and awareness about it. The prevalence of myths about the onset of diabetes was noticeably higher among diabetic patients. It was observed that a greater number of patients were shifting to alternative medications instead of allopathic ones, and in the long run, it can lead to various complications. Therefore, there is an immediate need to promote awareness about diabetes among the general population.

Introduction

Diabetes mellitus (DM) is one of the fastest-growing public health problems in the twenty-first century. According to the International Diabetes Federation (IDF) 10th edition, the prevalence of diabetes is 537 million in 2021, and it will exponentially rise to 643 million by 2030 and 783 million by 2045, out of which 50% of cases (i.e., one in two adults with diabetes) remain undiagnosed [ 1 ]. It was seen in a study that India ranks second, while China ranks first in the global diabetes epidemic [ 2 ]. India will have a prevalence of about 79.4 million diabetic cases by the year 2030 [ 3 ]. Many people (around 45%) remain undiagnosed for years and are later diagnosed as a case of type 2 DM [ 1 ].

The ignorance among people about their disease process may be related to their low socioeconomic status and lack of quality education available to them about the disease. Some people come to know about their disease once it has led to various complications like retinopathy, nephropathy, and neuropathy. Therefore, increasing awareness and education of people about the disease may help people to control their blood sugar levels and prevent its complications [ 4 ].

Diabetes is a serious condition leading to several complications if the individual does not follow up regularly for check-ups and blood sugar monitoring [ 5 ]. There are various treatment options available for diabetes such as insulin injections or insulin pumps in conjunction with continuous glucose monitoring technology for type 1 diabetes and oral hypoglycemic drugs for type 2 diabetes [ 6 ]. Lifestyle modifications such as a healthy diet, regular exercise, reducing weight, stress management, and smoking cessation can play a critical role in managing diabetes and improving the health and well-being of diabetic patients [ 7 ].

The aim of this study is to create awareness and knowledge about DM and its complications. The objectives of this study are to assess the awareness and knowledge about the disease, its complications, treatment preferences, lifestyle modifications, and self-monitoring of glucose among diabetic patients.

The rationale of this study was that most people in Haryana lack literacy and that diabetes is a significant non-communicable disease that affects a large number of people. It is the need of the hour to raise awareness about diabetes as the incidence of diabetes is increasing nowadays even in the younger age group.

Materials and methods

It was a hospital-based cross-sectional study on already diagnosed cases of DM. The study was conducted in Adesh Medical College and Hospital, Shahbad, over a period of two months from August 15, 2022, to October 15, 2022, with a sample size of 211 (duration based). The study was conducted after due approval from Institutional Ethics Committee for Biomedical and Health Research (IEC-BHR), Adesh Medical College and Hospital, Shahabad, Haryana, vide reference number AMCH/IEC-BHR/2022/08/01. The patients, aged 18 years or above of either gender, who had already been diagnosed with DM type 1 and type 2 were included, and the patients with gestational DM were excluded from the study.

Patients were included in the study after obtaining informed consent from them. A structured questionnaire was provided to the patients for obtaining demographic details like name, age, sex, occupation, education, and area of residence. It also had basic questions regarding knowledge and awareness of DM. Questions were interpreted by the interviewer to the patients, and forms were filled out according to the answers given by those patients. The form was in English language and interpreted by the interviewer in the local language (Hindi) to those who could not understand or read English. After obtaining all the answers, the level of knowledge and awareness was analyzed. All the data collected were kept confidential. The data were entered into an MS Excel sheet (Microsoft, Redmond, Washington) and analyzed by the Statistical Package for the Social Sciences (SPSS®) version 22.0 (IBM Corp., Armonk, NY). Categorical data were represented as percentages and frequencies. The mean age of diabetes was calculated in terms of mean ± standard deviation.

Demographic characteristics

The majority of our study sample, 51 patients (24%) who have an average age of 53.3 ± 16.4 years, falls within the age range of 51-60 years as shown in Table ​ Table1, 1 , while patients above 60 years of age made up 37.4% of the population and patients under 50 years of age made up 38.4%.

In our study, the maximum prevalence of diabetes was seen in males (55.5%) than in females (44.5%) as shown in underlying Table ​ Table2. 2 . As a result, males are more susceptible to disease than females.

In our study, participants from rural areas made up the majority (59%) compared to those from urban areas (41%) as shown in Table ​ Table3. 3 . Therefore, the rural population has more inclination toward DM than the urban population.

About 32% of patients, or the majority, had high school education; 27% of the patients completed middle school, whereas one-fourth (25%) of our study population was illiterate as shown in Table ​ Table4. 4 . Only 16% were educated to the graduation level.

About 84% of the 211 diabetic individuals were aware that having diabetes indicated having higher blood sugar levels as shown in Table ​ Table5, 5 , and 79% of patients were aware of the symptoms of DM, including frequent urination, increased thirst, persistent hunger, and unexpected weight loss. About 41% of patients were aware of diabetes-related complications, which include blurred vision, nerve damage, renal damage, and various issues with foot and oral health. Only 18% of the patients were aware of the symptoms of hypoglycemia.

DM: Diabetes mellitus.

Only 38% of the 211 patients possess their own glucometers and monitor their blood sugar levels on a regular basis, yet Table ​ Table6 6 reveals that 57% of those patients are unaware of typical fasting and postprandial blood sugar levels.

Merely 38% of the 211 diabetics were aware of the various DM treatment choices and duration of treatment as indicated in Table ​ Table7. About 7 . About 52% of the patients knew something about the insulin injections available for the treatment of diabetes.

Out of 211 patients, approximately half (49%) skipped their antidiabetic prescriptions, and of those, approximately half (22%) took a double dose the next day. About 121 patients (57%) combined the use of alternative medications along with allopathic medications, and of these 121 patients, 26 patients (22%) had replaced the allopathic medications with alternative medicines as indicated in Table ​ Table8 8 .

As shown in Table ​ Table9, 9 , almost 53% of patients had a positive family history of diabetes. About 54% of patients think that obesity and diabetes are unrelated, and although 79% of diabetics are aware of the lifestyle adjustments required to control their illness, they have not been able to incorporate these changes into their daily routines.

The majority of patients, nearly 67%, thought that diabetes could be cured permanently. Table ​ Table10 10 shows that 84% of patients thought that having diabetes was due to eating too much sugar.

DM, simply called diabetes, is a serious, long-term (or “chronic”) condition that is characterized by raised blood glucose levels because the body cannot produce any or enough of the hormone insulin or cannot effectively use the insulin it produces [ 1 ]. The typical symptoms are excessive thirst, frequent urination, lack of energy or fatigue, constant hunger, sudden weight loss, and blurred vision [ 1 ]. In our study, around 79% of the patients knew these symptoms of diabetes, and about 84% of patients answered that diabetes means raised blood glucose levels. The mean age of our study population was 53 ± 16 years, and the maximum number of patients in the age interval of 51-60 years is 24%. Age is one of the risk factors for the development of diabetes, and age ≥ 60 years is an independent risk factor for diabetes-related complications despite good control of cardiovascular risk factors [ 8 ]. In our study, 79 patients (37%) were aged above 60 years. Therefore, diabetes is more prevalent among the elderly, and similar data is seen in previous studies [ 9 , 10 ]. Another key risk factor for DM is a positive family history of diabetes. It is crucial to understand that people with a family history of diabetes are more knowledgeable about the signs and symptoms of the disease as well as the organs impacted by it than people without such a history. In a study conducted in 2017, it was found that in contrast to persons with negative family histories of DM, they experienced early-onset diabetes and were more likely to experience complications [ 11 ]. In our study, 53% of individuals were found to have a positive family history of DM out of which 26.4% of patients had knowledge and awareness about diabetes.

Obesity, particularly central obesity, is significantly linked to the onset and progression of type 2 diabetes. In a prior study, patients with type 2 DM had rates of overall obesity, abdominal obesity, and central obesity of 58.68%, 81.84%, and 53.42%, respectively [ 12 ]. About 46% of participants in our study were aware of the link between diabetes and obesity. As insulin sensitivity declines in fatty tissues, regulation of beta cell function also declines [ 13 , 14 ]. Increased levels of nonesterified fatty acids (NEFA), glycerol, hormones, cytokines, and pro-inflammatory chemicals in an obese person cause the development of insulin resistance [ 13 ].

The diagnosis of DM is made according to the criteria given by the American Diabetes Association (ADA) [ 15 ]. A 2020 meta-analysis by Dessie et al. found that a glucometer is significantly associated with higher medication adherence [ 16 ]. In our study, only 38% of the patients own a glucometer of their own and keep a check on their blood glucose levels on a regular basis, and 57% of patients do not even know about normal fasting and postprandial blood sugar levels.

In order to treat type 1 diabetes, the traditional method involves checking blood glucose levels manually, followed by daily subcutaneous insulin injections [ 17 ]. It has been demonstrated that using insulin pumps in conjunction with continuous glucose monitoring (CGM) technology lowers the long-term risks of diabetic complications [ 6 ]. Gene therapy is a novel approach to treating the disease, which offers a promising substitute for insulin injections since it tries to repair defective genes responsible for disease progression and thus prevents or reverses the development of the disease [ 17 , 18 ]. Particularly for type 1 DM, stem cell-based therapy has been viewed as a promising possible therapeutic approach for the management of diabetes [ 17 , 19 ]. For the treatment of type 2 DM, a variety of non-insulin-based oral treatments are available, including biguanides, insulin secretagogues, SGLT2 inhibitors, insulin sensitizers, etc. [ 20 ]. In our study, among 211 diabetics, only 38% of the patients were aware of the various treatment options for DM and duration of treatment, whereas about 52% of the patients had some awareness and knowledge about insulin therapy.

A study conducted by Benil et al. in 2003 showed that if a patient forgets to take the prior dose, almost 10% of patients had taken a double dose the next day. However, in our study, about half of the patients missed their antidiabetic medications out of which about 22% of them had taken a double dose on the next day. Also, 57% of patients used alternative medications along with allopathic medications, and 22% of them had replaced allopathic medications completely with alternative medications [ 21 ].

Human pluripotent stem cells are an appealing alternative beta cell source for transplantation. Beta cell replacement through islet of Langerhans transplantation is a potential treatment for DM, but the lack of donors prevents its widespread use [ 22 , 23 ]. The benefit upon transplantation is sometimes insufficient, and the transcript causes the functional ability to fall to 60% at 12 months [ 23 , 24 ]. Another suitable limitation that restricts its use is its pocket-draining expenses. After transplantation, the persistence of autoimmunity leads to a lifelong need for immunosuppression, which is a major drawback.

The most significant risk factors for the development of diabetes complications appear to be poor glycemic control and a protracted illness [ 25 ]. Diabetes complications affect almost every organ system. Diabetes complications fall into two categories, namely, microvascular and macrovascular. Microvascular issues include diabetic nephropathy, neuropathy, and retinopathy, whereas macrovascular complications include coronary artery disease, stroke, and peripheral vascular disease (PVD) leading to bruises and injuries which do not heal leading to gangrene and ultimately amputation [ 5 ]. One of the main barriers to restoring adequate metabolic control of the disease is hypoglycemia, which is the most prevalent acute complication in type 1 diabetes patients. In our study, about 41% of the patients were aware of the complications of DM. Only 18% of the patients were aware of the symptoms of hypoglycemia, i.e., fainting, tremors, convulsions, excessive hunger, etc.

A total of 3,200 participants in the National Diabetes Prevention Program (NDPP) of the United States were randomized to receive standard medical care, metformin therapy, or comprehensive lifestyle intervention. In order to attain a mean objective of 7% weight loss, the lifestyle intervention concentrated on reducing caloric intake by reducing fat calories and increasing physical activity to a goal of at least 150 min/per week [ 26 ]. The incidence of type 2 diabetes was shown to have decreased by 58% in the lifestyle intervention group, 31% in the metformin group, and 17% in the routine care group after an average of 2.8 years; thus, lifestyle modifications, i.e., exercise, dietary modifications, and smoking and alcohol cessation, play a major preventable therapy to reduce the disease burden [ 27 ]. In our study, around 22% of patients were still unaware of the beneficial and preventive effects of lifestyle modifications.

The majority of the patients believed the misconception that eating more sugar caused diabetes. In our study, 67% of people believe that diabetes can be cured permanently. Other beliefs about diabetes include the notions that it only develops in old age, that bathing your feet in water will help you manage your blood sugar, and that it is caused by your previous misdeeds and can only be treated spiritually [ 28 ]. Our study did not ask for any such specific beliefs; hence, there is no data for the same.

There could be several limitations of this study, which could have affected the final outcome. First, the study had highly heterogenous data in regard to the literacy, economic standards, and level of education of the participants involved. The fact that both type I and type II DM were included in the selection process could have a certain effect on the results. There is a possibility of reporting bias as this study was more focused on the knowledge and awareness among participants and not involved in an intervention-based approach. Although these limitations might have some indirect effect on the results, albeit having an insignificant effect on the objectives and final outcome of this study.

Conclusions

In our study, a significant number of patients suffering from diabetes had less knowledge and awareness about diabetes. The prevalence of myths like diabetes will be permanently cured after taking medications for some time and eating too much sugar causes diabetes was noticeably higher among diabetic patients. It was observed that a greater number of patients were shifting to alternative medications instead of allopathic ones, and in the long run, it can lead to more severe microvascular and macrovascular complications. There is an immediate need to promote awareness about diabetes among the general population with the help of community-based campaigns, collaborations with local media outlets, partnerships with healthcare providers, and optimal use of social media platforms. The stress should be made on early diagnosis and proper management, which are keys to preventing or delaying complications and improving the quality of life for patients with diabetes.

Questionnaire

Name:                                                              Age/Sex:

Education:                                                       Occupation:

Area of Residence: Rural/Urban

The authors have declared that no competing interests exist.

Human Ethics

Consent was obtained or waived by all participants in this study. Institutional Ethics Committee for Biomedical and Health Research (IEC-BHR), Adesh Medical College and Hospital issued approval AMCH/IEC-BHR/2022/08/01. The plan was approved for carrying out the study.

Animal Ethics

Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.

• Open access
• Published: 08 May 2024

Advances and challenges of the cell-based therapies among diabetic patients

• Ramin Raoufinia 1 , 2 ,
• Hamid Reza Rahimi 2 ,
• Ehsan Saburi 2 &
• Meysam Moghbeli   ORCID: orcid.org/0000-0001-9680-0309 2  

Journal of Translational Medicine volume  22 , Article number:  435 ( 2024 ) Cite this article

407 Accesses

Metrics details

Diabetes mellitus is a significant global public health challenge, with a rising prevalence and associated morbidity and mortality. Cell therapy has evolved over time and holds great potential in diabetes treatment. In the present review, we discussed the recent progresses in cell-based therapies for diabetes that provides an overview of islet and stem cell transplantation technologies used in clinical settings, highlighting their strengths and limitations. We also discussed immunomodulatory strategies employed in cell therapies. Therefore, this review highlights key progresses that pave the way to design transformative treatments to improve the life quality among diabetic patients.

Diabetes mellitus poses a formidable global public health challenge due to its rapid growing prevalence and associated morbidity, disability, and mortality [ 1 ]. According to the International Diabetes Federation, over 537 million adults aged 20–79 had diabetes worldwide in 2021 that is expected to rise to around 783 million cases by 2045 [ 2 ]. Obesity, unhealthy diets, physical inactivity as well as genetic and epigenetic predispositions are important risk factors of diabetes [ 3 , 4 , 5 ]. Diabetes is typically classified into type 1 diabetes mellitus (T1DM), gestational diabetes mellitus (GDM), and type 2 diabetes mellitus (T2DM) [ 2 ]. T1DM primarily arises from autoimmune-related damage of insulin-secreting beta cells, resulting in severe hyperglycemia and ketoacidosis [ 6 ]. In contrast, T2DM generally has a more gradual onset characterized by insulin resistance along with diminished compensatory insulin secretion from pancreatic beta cell dysfunction [ 7 ]. Diabetes is associated with macrovascular complications such as heart disease and stroke, as well as microvascular issues in eyes, kidneys, and nervous system [ 8 ]. Cancer is also a leading cause of diabetes-related death, and dementia-associated mortality has risen in recent decades [ 9 , 10 , 11 , 12 ]. Cell therapy involves transferring autologous or allogenic cellular material into patients [ 13 ]. The global market size of cell therapy is estimated to grow from $9.5 billion in 2021 to $23 billion by 2028 [ 14 ]. It combines stem and non-stem cell therapies consisting of unicellular or multicellular preparations. Cell therapies typically use autologous or allogenic cells via injection and infusion [ 15 ]. In the present review, we discussed the recent advances in cell-based therapy of diabetes, from foundational islet transplantation to regenerative strategies to highlight key developments that improve the effective treatments for diabetic patients.

Cell replacement therapy for diabetes

Pancreatic transplantation was firstly used in 1966 to treat type 1 diabetes using whole organ transplants. During the 1970s–80s, segmental pancreatic grafts were combined with techniques to divert digestive secretions away from transplanted cells. Three main techniques emerged; simultaneous pancreas-kidney transplants, pancreas transplants following kidney transplants, and pancreatic transplants. International collaboration on tracking outcomes began in 1980 with the formation of several pancreatic transplant registries and associations. However, whole organ transplantation was faced with several challenges including organ rejection, vascular complications, limited organ availability, and the effects of lifelong immunosuppression [ 16 , 17 ]. Islet cell transplantation was explored as an alternative, however isolating and transplanting pancreatic islets proved difficult due to donor availability, rejection, and immunosuppression side effects. Recent research has focused on stem cell sources that could reconstitute immune tolerance and preserve beta cell function such as mesenchymal stem cells, bone marrow cells, and embryonic stem cells [ 18 ]. A novel stem cell therapy called VX-880 was developed using proprietary technology to grow insulin-producing beta cells from allogeneic stem cells. Clinical trials began in 2021 after FDA approval to deliver the cells intrahepatically under immune suppression. A second approach called VX-264 encapsulates the same cells, avoiding immunosuppression but requiring surgical implantation [ 17 ]. In 2023, FDA approved the first allogeneic pancreatic islet cell therapy called Lantidra for adults with type 1 diabetes experiencing severe hypoglycemia. Approval was based on two studies where 21–30% of participants no longer required insulin one year post-treatment, with benefits lasting over five years in some cases. However, this treatment have mild and serious adverse events that are associated with treatment dose and the methods of islet cell infusion [ 19 , 20 ].

Emerging strategies for cell delivery via microencapsulation and biological devices in clinical trials

Alginate capsules as cell delivery systems.

A seminal investigation conducted in 1994 demonstrated the successful transplantation of alginate-encapsulated islets into the peritoneum of kidney transplant patients who were receiving immunosuppression therapy. Remarkably, these patients achieved insulin independence for up to nine months [ 21 ]. However, subsequent trials conducted without immunosuppression yielded inconsistent outcomes. In a study conducted in 2006, islets were encapsulated in triple-layer alginate capsules and implanted intraperitoneally in type 1 diabetes (T1D) patients. There was a positive correlation between the encapsulation and insulin production that reduced exogenous insulin requirements during one year. Despite this progress, the entry of cytokines remained a potential concern [ 22 ]. Another study employed the single-layer barium-alginate capsules that sustained insulin production for up to 2.5 years [ 23 ]. It has been reported that the microneedle, comprising a calcium alginate frame with polydopamine-coated poly-lactic-co-glycolic acid microspheres encapsulating insulin, enables light-triggered insulin release. Microneedle provided a suitable insulin dose to maintain blood glucose levels in line with daily fluctuations. These results established the efficacy and safety of the developed microneedle for diabetes treatment [ 24 ]. Another therapeutic approach explored the encapsulation of pancreatic islets with mesenchymal stem cells (MSCs) and decellularized pancreatic extracellular matrix (ECM). ECM derived from the pancreas supported islet cell growth and maintenance to enhance insulin expression [ 25 ]. Sodium alginate and hyaluronic acid were incorporated due to their roles in collagen production, wound healing, and physical crosslinking. The 3D porous membranes allowed optimal water and oxygen transfer while diverting excess exudate from diabetic wounds. Hydrogel accelerated re-epithelization, while decreased inflammation, indicating potential as the diabetic wound dressings [ 26 ]. Additionally, the incorporation of specific ECM components, such as collagen IV and RGD, into alginate-based microcapsules significantly improved the survival, insulin secretion, and longevity of microencapsulated islets [ 27 ].

Encaptra® device from ViaCyte

In contrast to microencapsulation techniques, ViaCyte developed a semipermeable pouch method named Encaptra, which contains pancreatic precursor cells derived from the embryonic stem cells [ 28 ]. In the initial trial conducted in 2014, the “VC-01” device was implanted in T1D individuals without the use of immunosuppression [ 29 ]. The trial confirmed the safety of the device; however, the occurrence of hypoxia induced cellular necrosis [ 30 ]. The device was modified as “VC-02” with larger pores, and two trials (NCT03162926, NCT03163511) demonstrated promising outcomes, including increased fasting C-peptide levels and a 20% reduction in insulin requirements during one year in the majority of participants [ 31 ]. In order to eliminate the necessity for immunosuppressants, ViaCyte collaborated with Gore to develop an expanded polytetrafluoroethylene (ePTFE) device with both immuno-isolating and pro-angiogenic properties [ 32 ]. This device (NCT04678557) aimed to prevent immune cell attachment and T-cell activation [ 33 ]. Additionally, ViaCyte is exploring the integration of CRISPR technology to modify stem cells, specifically by eliminating β2-microglobulin expression and PD-L1 up regulation. It is hypothesized that these genetic modifications will further hinder immune cell attachment and T-cell activation [ 30 , 34 ].

Semipermeable device from Semma therapeutics

Semma Therapeutics, which has been acquired by Vertex, pioneered the utilization of differentiated stem cell-derived islet cell clusters in clinical trials. Semma houses these cells between two semipermeable polyvinylidene fluoride membranes and is designed for subcutaneous implantation (NCT04786262) [ 31 , 35 ]. Vertex reported a significant breakthrough by infusing differentiated beta cells via the portal vein in a participant who was receiving immunosuppressants. This approach led to substantial C-peptide production and improved glycemic control during 90 days [ 36 ].

βAir device from Beta O2

Beta O2’s innovative βAir device utilizes an alginate-PTFE membrane complex to encapsulate islets, providing partial immunoisolation while ensuring a continuous supply of oxygen, which is crucial for optimal islet function [ 37 , 38 ]. The βAir device that was seeded with human islets was subcutaneously implanted in T1D individuals (NCT02064309). Although, low insulin levels were produced for up to eight weeks, there was not any reduction in the required exogenous insulin [ 37 ]. While, increasing the number of islets could potentially enhance their function, it is important to note that the continuous reliance on oxygen poses a risk of infection, despite efforts to optimize the survival of encapsulated islets [ 39 , 40 ].

Cell pouch™ device from Sernova

Sernova has developed the Cell Pouch device, which offers pre-vascularized polypropylene chambers for islet transplantation without the need for immunoprotection. The device consists of multiple cylindrical chambers that are prefilled with PTFE plugs, which are then removed after implantation to create the empty space [ 41 ]. In a 2012 trial (NCT01652911), islets were placed in the vascularized pouches of three recipients who were also receiving immunosuppression that resulted in a transient increase in C-peptide levels [ 41 ]. In a 2018 trial (NCT03513939), immunosuppression was administered after implantation and islet introduction. This trial reported sustained C-peptide production for up to nine months in two recipients, along with improved glycemic control [ 42 ]. Regarding the limitations of immunosuppression, Sernova is exploring the possibility of encapsulating islets in hydrogel as an alternative approach [ 43 ].

Shielded living therapeutics™ from Sigilon Therapeutics

Sigilon has developed the Shielded Living Therapeutics sphere, which consists of cell clusters enclosed within an alginate-TMTD coating [ 44 ]. Preclinical studies demonstrated that murine islet transplants encapsulated within these spheres maintained normoglycemia for a period of six months [ 45 ]. In a 2020 trial conducted for hemophilia (NCT04541628), the spheres were evaluated for their ability to express Factor VIII [ 46 ]. However, the trial was paused due to the development of antibodies in the third recipient receiving the highest cell doses. While, preclinical studies have shown promising efficacy, there are safety concerns regarding the TMTD coating that need to be addressed before these spheres can be used for human islet transplantation as a treatment for diabetes [ 31 ]. Emerging technologies have been investigated in clinical trials for delivering insulin-producing islets or stem cell-derived beta cells via microencapsulation or use of implantable biological devices (Table 1). Optimizing encapsulation and developing alternative implantable devices moves the field toward delivering safe and effective islet replacement without chronic immunosuppression dependency that represented an important new frontier for the cell-based treatment of diabetes. However, continued refining will be required to fully realize this promising vision and using these preclinical concepts in clinic.

Immunoengineering strategies: biomaterials for modulating immune responses

Islet encapsulation aims to prevent immune responses toward transplant antigens. However, foreign body response (FBR) against biomaterials induces inflammation around encapsulated islets that obstructs oxygen/nutrient access and causes graft failure [ 31 ]. Extensive research revealed biomaterial properties profoundly influence FBR severity, with high purity/biocompatibility moderating inflammation [ 47 ]. Deeper understanding of biomaterial immunobiology enabled developing immune-modulating constructs to steer host interactions. By altering topology/chemistry to hinder nonspecific binding and cell adhesion, these “immune-evasive biomaterials” intended to attenuate xenograft rejection at inception [ 44 ]. Both innate and adaptive immune responses have crucial roles in the context of pancreatic islet transplantation. These responses encompass the activation of tissue macrophages and neutrophils following injury, leading to the release of inflammatory cytokines that subsequently activate antigen-presenting cells (APCs), CD8 + T cells, CD4 + T cells, and cytotoxic T lymphocytes (Fig.  1 ). Zwitterionic polymers conferred anti-fouling attributes but crosslinking limitations constrained their application [ 48 ]. Novel mild zwitterionization introduced alginate modifications that prolonged prevention of fibrotic overgrowth by mitigating initial responses [ 49 , 50 , 51 ]. The prevention of graft rejection following islet cell transplantation necessitates the systemic administration of immunosuppressive agents. While, these agents effectively suppress immune responses, their continuous use exposes patients to an increased risk of infection and cancer. To mitigate these concerns, an alternative approach involving the localized delivery of immunosuppressants at the transplantation site has emerged. This localized delivery system offers several advantages, including targeted drug delivery, reduced systemic exposure, and potentially reduces the immunosuppressants doses [ 52 ]. Polymeric carriers dispersed cyclosporine A continuously at the graft site to dynamically tamp down proinflammatory cascades and T-cell activation [ 53 , 54 ]. TGF-β/IL-10 co-delivery at the microencapsulation interface hindered innate antigen presentation, obstructing adaptive response priming [ 55 , 56 ]. Regulatory T-cells emerged as the potent immunomodulators when coated on islets to improve insulin production in vitro [ 57 ]. Similarly, recombinant Jagged-1 surface patterning increased regulatory lymphocytes in vitro while enhancing glycemic oversight in vivo [ 58 ]. Targeting proinflammatory effector T-cells or presenting their Fas ligand death receptor improved long-term viability when combined with rapamycin prophylaxis [ 52 , 59 ]. Immobilizing thrombomodulin or urokinase mitigated local inflammation, with the latter conferring lifelong xenotransplant survival [ 60 ]. Peptides recognizing IL-1 receptors provided robust protection from destabilizing proinflammatory cytokines [ 61 ]. Leukemia inhibiting factor improved islet performance over polyethylene glycol encapsulation alone by inducing regulatory T-cell lineages [ 62 ]. Silk scaffolds facilitated IL-4/dexamethasone emancipation that meaningfully decreased immune reactions to grafts [ 63 ]. Therefore, the localized delivery of immunosuppressants at the transplantation site represents a promising strategy for islet cell transplantation. Compared to systemic administration, local delivery can achieve targeted immune modulation only at the graft location while reducing drug exposure throughout the body. This localized approach aims to sufficiently suppress the immune response to prevent rejection, while limiting negative side effects that may occur from systemic immunosuppression. A variety of biomaterials and surface modification strategies have been developed and investigated for the local delivery of immunosuppressive agents and immunomodulatory cytokines [ 64 , 65 , 66 ]. Understanding how biomaterial properties influence the immune response is critical to design biomaterials that can modulate inflammation and improve islet graft survival through localized immunomodulation.

Cell-based therapy through the integration of additive manufacturing techniques

Additive manufacturing utilizes computer modeling to fabricate complex 3D structures on-site with minimal post-processing. Common methods for the biomedical application are fused filament fabrication (FFF), stereolithography (SLA), and bioprinting [ 67 ]. FFF is a layer-by-layer technique that extrudes heated thermoplastics [ 68 ]. Commonly used feedstocks include acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA). Other thermoplastics that have been utilized with FDM include thermoplastic polyurethane (TPU), polycarbonate (PC), polystyrene (PS), polyetherimide (PEI), polycaprolactone (PCL), polyaryletherketone (PAEK), and polyetheretherketone (PEEK), with the latter demonstrating high strength and heat tolerance. A major advantage of FDM is its ability to fabricate multi-material objects through continuous printing and alteration of the build material. In addition to typical polymers like PC and polystyrene (PS), FDM can print composites reinforced with glass, metals, ceramics, and bioresorbable polymers via integration of the constituent powders with a binding matrix. This enables enhanced control over the experimental component fabrication. While, ceramic and metal filaments traditionally contain the corresponding powder mixed with a binder, FDM provides versatility in the functional prototype construction from a wide range of thermoplastic feedstocks using precise and additive layer manufacture [ 68 , 69 , 70 , 71 , 72 ]. It provides geometric reproducibility and reduced variability compared to traditional techniques. FFF prints served as scaffolds for the transplanted cells [ 67 ]. However, minimum feature size is limited to ? ∼  250 μm by nozzle diameter [ 68 ]. SLA employs light-curable liquid resins and achieves higher 50–150 μm resolution than FFF but with restricted material choices. Bone grafts and surgical guides are common applications [ 67 ]. Incorporating biomaterials like hydroxyapatite has expanded utility, though processing is required to mitigate cytotoxicity. Additive manufacturing can address limitations in oxygen transport, cell/material placement control and vasculature formation, and clinically translatable insulin-secreting implants [ 67 ]. Therefore, additive manufacturing technologies have the potential to enhance various aspects of the cell-based transplant design, from improving nutrient transport through optimized implant geometry to achieving precision integration of therapeutic agents (Table 2).

Enhancing nutrient transport through optimization of implant geometry

Tissue engineering for the islet transplantation requires maximizing nutrient transport [ 73 , 74 ]. Traditional scaffold fabrication introduces macroporosity but lacks precision that results in inflammation [ 67 ]. Cell encapsulation provides immunoprotection by limiting interactions between transplanted cells and the host immune system. However, this protective barrier also poses challenges for the efficient transport of essential nutrients, including oxygen, to the encapsulated cells. Modifying the geometries of encapsulation devices using conventional methods to enhance oxygen delivery has proven to be inconsistently challenging [ 67 ], so that novel approaches are required to address these challenges. Additive manufacturing allows customizing biomaterial scaffolds with defined geometries and micropore sizes to improve transport [ 75 , 76 , 77 , 78 , 79 ]. The 3D printed PLA scaffolds with islets have successful vascularization and cellular survival after subcutaneous transplantation [ 80 , 81 ]. Interlocking toroidal hydrogel-elastomer constructs also increased surface area and cell viability [ 82 , 83 , 84 ].

Enhancing vascularization and engraftment

Rich host vascularization of transplant devices is essential to support long-term islet survival through efficient nutrient delivery and insulin kinetics. Early platforms modified bulk material properties to promote vessel infiltration and anastomoses [ 85 , 86 , 87 , 88 , 89 ]. Additive manufacturing can further optimize microscale geometry to both accelerate host vessel connections and control intra-device vasculature homogeneity beyond traditional fabrication. Initial work reproduced macroscale vessels but scales were diverged from cell-based therapies [ 73 , 90 , 91 , 92 ]. Leveraging Additive manufacturing designed structures guided vessel formation in vitro and in vivo [ 80 , 89 , 93 ]. Shifting to bioprinting complex branching conduits in supportive hydrogels facilitated clinical translation for diverse cell therapies [ 94 , 95 , 96 , 97 , 98 ]. Researchers focused on developing a 3D scaffold platform to improve the transplantation outcomes of islet cells in T1D. The scaffold featured a heparinized surface and immobilized vascular endothelial growth factor (VEGF) to enhance vascularization. Scaffold effectively promoted angiogenesis and facilitated the growth of new blood vessels. Additionally, encapsulated islets within the scaffold had functional responses to glucose stimuli. These findings suggested that the developed scaffold platform holds potential for successful extra-hepatic islet transplantation, offering new possibilities for T1D treatment [ 99 ]. Research on vascularization of islets via additive manufacturing techniques has primarily focused on the fundamental discoveries. In one study, engineered pseudo islets (EPIs) were created by combining the mouse insulin-secreting beta cells with rat heart microvascular endothelial cells. EPIs demonstrated extensive outgrowth of capillaries into the surrounding matrix. Although, EPIs containing both cell types that underwent capillarization maintained viability and function over time in culture, non-vascularized EPIs lacking endothelial cells could not sustain viability or functionality long-term. This supported the potential for inducing angiogenesis within bioengineered islet constructs. Future work may combine patient-specific stem cell-derived human beta cells with endothelial cells using this approach to promote long-term graft survival for treating type 1 diabetes [ 98 ]. While, large-scale 3D printed vascularized structures are currently limited for the islet transplantation, advancements in leveraging additive manufacturing for the optimization vascularization conditions through the pore sizes and material choices, may facilitate translation to β-cell therapy in type 1 diabetes.

Precision placement of cells and matrix for enhanced control

Beyond distributing biomaterials, additive manufacturing enables micro-level cell and protein control. For islet transplantation, optimal cellular distribution and supportive extracellular matrix niche reduce rapid dysfunction and apoptosis [ 100 , 101 , 102 ]. Traditional techniques heterogeneously load cells after fabrication or struggle with incomplete encapsulation [ 103 , 104 ]. Bioprinting allows in situ encapsulation and printing of multiple cell types and matrix components while dictating 3D placement and dimensions [ 105 , 106 ]. Islet transplant research prints hydrogel-encapsulated clusters surrounded by supportive cells and doped with immune modulators to improve the transplant environment [ 107 ]. Progress in bioprinting offers consistency and defines physical/chemical graft properties beyond traditional fabrication.

Achieving controlled integration of therapeutic agents for enhanced efficacy

In addition to the cell and matrix placement, additive manufacturing enables precision therapeutic integration. Incorporating therapeutics aims to recapitulate the in vivo environment through angiogenesis, islet health promotion, and immunomodulation [ 67 , 108 ]. Growth factors promote vessel formation and insulin secretion while decrease apoptosis [ 108 , 109 , 110 , 111 ]. Local immunomodulators regulate the immune system in a specific site of the body. They decrease inflammation and promote the successful integration of transplanted cells or tissues by minimizing the need for widespread immune suppression in whole body [ 67 ]. Traditional homogeneous delivery methods restrict the ability to customize the spatial distribution of substances and pose a risk of harmful effects on transplants or hosts [ 112 ]. The use of discreet gradients in bioprinting can offer precise physiological signals. By combining traditional drug release methods with AM, it becomes possible to create tissues that exhibit distinct therapeutic localization. Bioprinted composites have the ability to release factors with gradients throughout the entire construct that enables a more comprehensive and targeted approach in tissue engineering [ 112 , 113 , 114 ].

Cell based gene therapy

Gene therapy holds great promise for diabetes management, offering innovative approaches to deliver and manipulate the insulin gene in various tissues. Viral methods, such as lentivirus, adenovirus, and adeno-associated virus (AAV), along with non-viral techniques like liposomes and naked DNA, have been utilized to deliver the insulin gene to target tissues [ 115 ]. This section aims to provide an overview of important studies in the field of gene therapy for diabetes management, emphasizing advancements in insulin gene delivery and manipulation (Table 3).

Enteroendocrine K-cells and pancreatic β-cells

Enteroendocrine K-cells in the intestines and pancreatic β-cells share similarities in their production of glucose-dependent insulinotropic polypeptide (GIP) and their regulatory mechanisms. Understanding these similarities offers insights into T2D management and improving glucose homeostasis. However, attempts to reverse diabetes effectively through K-cell transplantation have been unsuccessful. Nevertheless, research on gene editing techniques has shown promising results in management of the diabetes mellitus [ 116 , 117 ]. AAV vectors have been employed to co-express insulin and glucokinase genes in skeletal muscles, demonstrating long-term effectiveness in achieving normo-glycemia without exogenous insulin [ 118 , 119 ].

Gene editing techniques

Gene editing techniques using AAV vectors effectively improved normo-glycemia in animal models. Co-expression of insulin and glucokinase in transgenic mice increased glucose absorption and regulated insulin production. Duodenal homeobox 1 (PDX1) gene transfer via AAV2 in a humanized liver mouse model also led to insulin secretion and glycemic control [ 120 ]. Adenovirus-mediated transfection of hepatic cells with neurogenin 3 (NGN3) resulted in insulin production and trans-differentiation of oval cell populations [ 121 , 122 ]. Targeting specific promoters in liver cells such as phosphoenolpyruvate carboxykinase (PEPCK), glucose 6-phosphatase (G6Pase), albumin, and insulin-like growth factor binding protein-1 (IGFBP-1) enhanced hepatic insulin gene therapy [ 123 , 124 ]. AAV-mediated overexpression of SIRT1 reduced inflammation, hypoxia, apoptosis and improved neural function in the retina of diabetic db/db mice [ 125 ]. Another study developed a plasmid expressing a single-strand insulin analogue for intramuscular injection using a specialized gene delivery technique. A single administration provided sustained insulin expression for 1.5 months and effectively regulated blood glucose levels without immune responses or tissue damage in diabetic mice.

Non-viral gene delivery methods

Non-viral approaches have also key roles in achieving glycemic control. The combination of insulin fragments with DNA plasmid, administered via intravenous injection improved normo-glycemia for extended periods. DNA transposon facilitated gene integration into the host chromosome that addressed the short-term liver expression. Additionally, the co-injection of DNA plasmid containing insulin with furin significantly enhanced insulin production within muscles [ 126 ]. Non-viral plasmids were engineered to carry proinsulin and pancreatic regenerating genes to ameliorate streptozotocin-induced T1DM [ 127 ]. The pVAX plasmid vectors prolonged therapeutic effects in achieving normo-glycemia without the need for further treatment [ 127 ]. Bioreducible cationic polymers, such as poly-(cystamine bisacrylamide-diamino hexane) (p(CBA-DAH)), have been employed to deliver RAE-1 to pancreatic islets, resulting in improved insulin levels [ 128 ]. Furthermore, ex vivo gene transfer and autologous grafts have shown promising outcomes in animal models. The introduction of the human insulin gene into pancreatic or liver cells followed by autologous grafts improved insulin secretion, glycemic control, and alleviated the diabetic complications in pigs. However, gene silencing eventually occurred, necessitating a deeper understanding of the underlying mechanisms [ 128 , 129 ].

Stem cell based therapy in diabetes

Efforts are ongoing to develop standardized processes for donor and recipient selection/allocation to increase pancreas utilization [ 130 , 131 , 132 , 133 ]. Techniques for isolating pancreatic islets are being optimized to become more standardized and consistent. Noninvasive imaging technologies allow the monitoring of the transplanted islets without surgery [ 134 , 135 ]. Biomarkers could also evaluate how immunomodulation strategies are working [ 136 , 137 , 138 ]. Researchers are also exploring alternative transplant sites in the body beyond just the liver, to see if the other locations may better support islet graft survival and function. Together, these areas of refinement aim to improve the safety and reliability of islet transplantation procedures as a potential therapy for diabetes [ 139 ]. Bioengineering approaches are being developed to optimize the islet transplantation microenvironment using biomaterials which enhance islet engraftment and function through engineered extracellular niches [ 140 , 141 ]. For example, encapsulation techniques aim to protect pancreatic islets against immune reponse by enclosing them within semipermeable hydrogel polymer capsules [ 142 , 143 ]. This localized immunoisolation strategy utilizes biomaterials like alginate to create a physical barrier preventing immune cell contact while still allowing nutrient and oxygen diffusion. Researchers concurrently seek alternative unlimited cellular sources to address limited islet availability. Mesenchymal stem cells possess immunomodulatory properties and their adjuvant delivery, either early in disease onset or simultaneously with islet transplantation, has shown promising signs of improving outcomes in preclinical investigations. By dampening inflammatory responses and favoring regenerative processes, stem cells may help to establish a more tolerogenic transplant environment. These bioengineering and cell therapy approaches offer potential pathways towards eliminating the exogenous insulin requirement [ 144 , 145 ]. A variety of stem cell types have therapeutic potential for diabetes (Fig.  2 ). Pluripotent stem cells possess immense promise for overcoming the limitations of islet transplantation. Human embryonic stem cells and induced pluripotent stem cells are especially attractive candidates due to their unique ability to both self-renew indefinitely and differentiate into any cell type. This makes them an ideal source of replacement pancreatic beta cells. Significant research effort across academic and industrial laboratories has led to advancement in differentiation protocols that can convert pluripotent stem cells into functional beta-like cells in vitro. However, establishing consistent, well-characterized cellular production methods that comply with stringent safety and efficacy standards remains a priority for clinical translation. Ongoing work aims to generate therapeutic stem cell-derived beta cell replacements exhibiting stable, glucose-responsive insulin secretion comparable to primary islets. Although, technological and regulatory hurdles still must be cleared, pluripotent stem cells have the greatest potential to finally solve the problem of limited cell availability and provide an unlimited source of transplantable tissue suitable for widespread treatment of diabetes [ 145 , 146 , 147 , 148 ]. There are currently six registered clinical trials evaluating the use of human pluripotent stem cells for the T1D treatment. All trials except one use PEC-01 cells, which consist of a mixture of pancreatic endoderm and polyhormonal cell population derived from CyT49 stem cells that are fully committed to endocrine differentiation upon implantation [ 149 ]. The initial trial implanted PEC-01 cells within an encapsulation device, hypothesizing no need for immunosuppression. While, well-tolerated with minor adverse effects, insufficient engraftment occurred due to foreign body responses that eliminated the cells [ 150 ]. The trial transitioned in 2017 to use an open encapsulation device that required immunosuppression. Subcutaneous engraftment, differentiation of cells into islet-like clusters, and glucose-responsive insulin production provided the first evidence that pancreatic progenitor cells can survive, mature, and function as the endocrine cells in humans. Potential benefits on stimulated C-peptide levels and glycemic control were observed in one patient [ 151 , 152 ]. Two reports in late 2021 described results in 17 patients receiving PEC-01 cells in an open device. Engraftment and insulin expression occurred in the majority, glucose-responsive secretion in over one-third, and various glycemic improvements were observed at six months. Explanted tissues contained heterogeneous pancreatic compositions including mature beta cells, with no teratoma formation and mild adverse effects related to surgery/immunosuppression. VX-880 uses fully differentiated insulin-producing stem cell-derived islet cells in phase 1/2 trial evaluating portal infusion and different doses requiring immunosuppression. Preliminary results suggest early engraftment and insulin secretion. The manin challenge was controlling immune rejection without systemic immunosuppression [ 149 ]. Several strategies are being explored to address the challenges of immune rejection in stem cell therapies for diabetes. They include generating stem cell lines that are universally compatible through HLA silencing, developing milder regimens of immunosuppression, and refining encapsulation and containment approaches to protect transplanted cells toward immune response. Establishing standardized stem cell banks is also an area of investigation [ 153 , 154 ]. Xenotransplantation using gene-edited porcine islets remains an exciting avenue of research given advances to improve engraftment and reduce immunogenicity in preclinical studies [ 155 ]. Novel approaches continue to emerge as well, such as decellularization techniques, 3D bioprinting of tissue constructs, and creating interspecies chimeras. Rapid evolution of cell-based therapies across both academic and commercial sectors is promising to restore normoglycemic control in diabetic cases. Refinement of existing methods and development of new strategies hold potential to perform a safe and effective cell replacement without reliance on systemic immunosuppression. Stem cell and regenerative therapies may ultimately manage diabetes through restored endogenous insulin production [ 156 ]. Recently a meta analysis evaluated the safety and efficacy of MSC-based therapy for diabetes in humans. This comprehensive analysis was conducted on 262 patients across six trials that met the inclusion criteria within the last five years. The results reveal that treatment with MSCs significantly reduced the dosage of anti-diabetic drugs over a 12-months. Following treatment, HbAc1 levels decreased by an average of 32%, fasting blood glucose levels decreased by an average of 45%, and C-peptide levels showed a decrease of 38% in two trials and an increase of 36% in four trials. Notably, no severe adverse events were reported across all trials. Therefore, it can be concluded that MSC therapy for type 2 diabetes is safe and effective [ 157 ].

Advances in islet transplantation and stem cell-derived Beta cells

Limited number of the islet transplantation donors highlights the importance of cell therapy in diabetes. Although, higher islet numbers from multiple donors increase the success, limited pancreas availability restricts widespread use [ 158 ]. Using multiple donors also increases rejection risk, while isolation of the islets can cause tissue damage [ 159 ]. To overcome these challenges, researchers have explored the differentiation of stem cells into beta cells in vitro to generate an unlimited supply of insulin-producing cells with standardized and characterized products. Genetic engineering techniques have also been investigated to confer advantages such as stress resistance or immune evasion [ 158 ]. ViaCyte has developed a stem cell-derived pancreatic progenitor called PEC-01, which has the ability to mature into endocrine cells in rodent models. To protect the transplanted cells from immune response, retrieval encapsulation devices were also created [ 160 , 161 , 162 ]. In an initial human clinical trial conducted in 2014 (NCT02239354), the Encaptra device was utilized with the aim of providing complete immunoprotection of transplanted cells through the use of a cell-impermeable membrane. Although, the PEC-Encap product showed reliable tolerance and minimal adverse effects, the trial was stopped due to the inadequate engraftment of functional products. While, a few endocrine cells were observed, fibrosis around the capsule led to graft loss and supression of the insulin secretion. To address this challenge, a more recent development called the PEC-Direct device was introduced, which featured openings in the membrane to facilitate vascularization, thereby improving nutrient exchange and supporting cell viability. However, since host cells could infiltrate the device, immunosuppression was necessary following the transplantation [ 163 , 164 , 165 ]. Protocols were developed to generate clusters of stem cell-derived beta cells that secreted glucose-responsive insulin. These clusters, referred to SC-islets, also contained other endocrine cells, including glucagon-producing cells. SC-islets improved glycemic control in diabetic mice and nonhuman primates [ 146 , 166 , 167 , 168 ]. In a trial conducted in 2017 (NCT03163511), the transplantation of progenitor cells resulted in the maturation of endocrine cells, and glucose-responsive C-peptide secretion was observed 6–9 months post-transplantation. Notably, the majority of these mature endocrine cells exhibited glucagon-positive characteristics. The porous regions housing the endocrine cells allowed for the infiltration of host vessels to facilitate vascularization. However, non-cellular regions were isolated by the presence of fibrosis [ 164 , 165 ]. Although, there was not a sufficient levels of circulating C-peptide in these trials, the findings underscored the significance of promoting vascularization and minimizing fibrotic reactions [ 164 , 169 ]. Vertex conducted a human trial in 2021 (NCT04786262) involving the transplantation of half-dose VX-880 cells (SC-islets) without a device to avoid previous problems, which necessitated immunosuppression. Preliminary results reported improved glycemic control, although it took longer to achieve the same outcome compared to rodent models [ 158 ]. Overall, progresses in islet transplantation and stem cell-derived beta cells pave the way for overcoming the limitations of traditional approaches. Further research and refinements are also required to achieve consistent and clinically significant outcomes in the treatment of diabetes.

Chalenges and limitations

Cell-based therapies have been significantly progressed for diabetes; however, there are still several challenges that need to be overcome. Clinical trials investigating encapsulation devices and islet transplantation techniques have provided valuable insights but face several obstacles including oxygenation, host immune responses, and insufficient long-term engraftment success. Immunoengineering of biomaterials and additive manufacturing for the development of 3D islet structures aim to modulate inflammation and promote graft revascularization. Nevertheless, achieving consistent normalization of blood glucose levels without exogenous insulin remains a challenge in human studies. In the field of gene therapy and stem cell differentiation, research focuses on genetically-modified or progenitor-derived insulin-secreting β-like cells to optimize protocols that ensure safety and functionality. The main challenge is to establish stable and functional cells capable of permanently restoring normoglycemia without the need for external intervention. One major barrier is the immune response, which targets allogeneic and xenogeneic islet grafts. Although, local immunotherapy minimizes the systemic effects, evading graft destruction through biomaterials without the requirement of immune suppression remains a significant challenge. The translation of precision 3D islet constructs and genetically reprogrammed cells also necessitates scalable manufacturing processes to ensure consistent function and long-term safety across batches. When critically appraising progress in the field of cell-based diabetes treatments, it is imperative to consider the regulatory, ethical, economic, and safety factors that shape translational applications. At the regulatory level, oversight bodies play a pivotal role in establishing standards to ensure patient welfare while enabling therapeutic innovation. FDA oversees clinical trials and product approvals in the United States (US), while in Europe the EMA provides parallel regulatory guidance. Within the US, organizations like the United Network for Organ Sharing (UNOS) and Organ Procurement and Transplantation Network (OPTN) govern organ and cell allocation protocols [ 17 , 170 ]. However, as regenerative approaches diverge from traditional organ transplantation, regulatory pathways require ongoing harmonization between the agencies and jurisdictions. Continual dialogue between researchers, oversight boards, and policymakers will be crucial to streamline guidelines in a patient-centric manner that balances safety, efficacy, and timely access to cutting-edge therapies. For instance, as stem cell-derived beta cells and 3D bioprinted tissue constructs emerge, traditional drug and device frameworks may not adequately address product characterization and manufacturing complexities for these advanced therapeutic products [ 67 ]. Within clinics, maintaining compliance with evolving regulations impacts research directives and ultimately patients’ access to the novel treatments. Addressing informed consent, clinical trial design, and privacy protections for sensitive health data are also paramount from an ethical perspective [ 128 , 129 ]. Autonomy and agency of research participants in decision-making related to experimental therapies demand prudency. Equitable accessibility of new treatment options also warrants attention to avoid certain populations facing undue barriers. Cell sourcing presents ethical issues depending on derivation from embryonic, fetal or adult tissues. Logistical matters like shipping and processing stem cell-derived islets prior to transplantation necessitate scrutiny. Tumorigenic potential of the undifferentiated pluripotent stem cells should be optimized through rigorous preclinical testing. Transitioning therapies between animal and early human investigations necessitates well-characterized cellular products showing consistent safety and glucose-responsive insulin secretion profiles comparable to pancreatic islets. Long-term animal model data substantiating lack of malignant transformation following transplantation aids allaying ethical safety concerns as the therapies progress clinically. Researchers carefully screen new concepts to prevent side effects in participants while pursuing curative goals. In terms of economic costs, islet and stem cell transplant procedures remain prohibitively expensive for broad applicability despite promising clinical signals. The field requires sustained study to validate techniques, track long-term outcomes, assess healthcare costs offsets from mitigating diabetes’ debilitating complications, and establish cost-benefit ratios for national reimbursement paradigms. Public-private partnerships may accelerate large, interventional trials and longitudinal research to precisely quantify the cellular therapies’ safety profiles and real-world efficacies compared to intensive management versus costs of intensive diabetes care. Ongoing developments like 3D bioprinting offer catalytic manufacturing potential fundamentally recalibrating economics by enhancing yields, standardizing procedures, and reducing costs through scale. By thoroughly and sensitively examining regulatory frameworks, informed consent processes, risks and benefits, as well as financial considerations at both micro and macro levels, researchers, oversight boards and broader stakeholder networks can advance cell-based therapies towards delivering life-changing benefits for all communities. A multidisciplinary, conscientious approach balances progress against patient welfare. A combination of multiple strategies may help to overcome these limitations. For instance, gene-modified islets integrated within vascularized biomaterial implants or sequenced therapies have promising results to prime grafts in pro-regenerative environments before transplantation. Collaboration across disciplines offers hope that refined individualized therapies may eventually achieve durable insulin independence through functional pancreatic cell or tissue engraftment, not only for diabetes but also for chronic pancreatitis. Regarding, ongoing progresses in unraveling these barriers, cell replacement approaches have the potential to improve diabetes management.

Conclusions

This review provides a comprehensive overview of the advances, challenges, and future directions in various cell-based therapeutic approaches for the treatment of diabetes. Significant progresses have been achieved in microencapsulation design, immunomodulation, tissue constructs, genetic and cellular reprogramming techniques, as well as initial clinical translation. However, the complete restoration of normoglycemia without the need for lifelong immunosuppression is still considered as a significant therapeutic challenge. Therefore, addressing the transplant environment of the hostile nature, developing minimally invasive delivery methods, and overcoming limitations in engraftment efficiency and longevity are crucial issues for the future researches. Through the sustained multidisciplinary efforts for the improvement of existing strategies and establishing novel paradigms, achieving durable insulin independence can be a realistic goal for all diabetic cases through the personalized cell replacement or regeneration.

Immune Responses toward pancreatic islets following transplantation. This figure illustrates the immune responses, including the innate and adaptive immunity that are triggered upon pancreatic islet transplantation. Immune response begins with the activation of tissue macrophages and neutrophils in response to injury. Subsequent, release of inflammatory cytokines stimulates antigen-presenting cells (APCs), CD4 + T cells, CD8 + T cells, and cytotoxic T lymphocytes to orchestrate the immune response

Potential stem cell sources for the treatment of diabetes

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Acrylonitrile butadiene styrene

Activate antigen-presenting cells

Adeno-associated virus

Duodenal homeobox 1

Engineered pseudo islets

Expanded polytetrafluoroethylene

Extracellular matrix

Foreign body response

Fused filament fabrication

Gestational diabetes mellitus

Glucose 6-phosphatase

Insulin-like growth factor binding protein-1

Mesenchymal stem cells

Neurogenin 3

Organ Procurement and Transplantation Network

Phosphoenolpyruvate carboxykinase

Polyaryletherketone

Polycaprolactone

Polycarbonate

Polyetheretherketone

Polyetherimide

Poly-lactic acid

Polystyrene

Stereolithography

Thermoplastic polyurethane

Type 1 diabetes

Type 1 diabetes mellitus

Type 2 diabetes mellitus

United Network for Organ Sharing

United States

Vascular endothelial growth factor

Vos T, Lim SS, Abbafati C, Abbas KM, Abbasi M, Abbasifard M, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of Disease Study 2019. Lancet. 2020;396(10258):1204–22.

Article   Google Scholar  

Cho NH, Shaw J, Karuranga S, Huang Y, da Rocha Fernandes J, Ohlrogge A, et al. IDF Diabetes Atlas: global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract. 2018;138:271–81.

Article   CAS   PubMed   Google Scholar  

Moghbeli M, Naghibzadeh B, Ghahraman M, Fatemi S, Taghavi M, Vakili R, et al. Mutations in HNF1A gene are not a Common cause of familial young-onset diabetes in Iran. Indian J Clin Biochem. 2018;33(1):91–5.

Akhlaghipour I, Bina AR, Mogharrabi MR, Fanoodi A, Ebrahimian AR, Khojasteh Kaffash S, et al. Single-nucleotide polymorphisms as important risk factors of diabetes among Middle East population. Hum Genomics. 2022;16(1):11.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Moghbeli M, Khedmatgozar H, Yadegari M, Avan A, Ferns GA, Ghayour Mobarhan M. Cytokines and the immune response in obesity-related disorders. Adv Clin Chem. 2021;101:135–68.

Eizirik DL, Pasquali L, Cnop M. Pancreatic β-cells in type 1 and type 2 diabetes mellitus: different pathways to failure. Nat Reviews Endocrinol. 2020;16(7):349–62.

Article   CAS   Google Scholar  

Siqueira ISLd, Alves Guimarães R, Mamed SN, Santos TAP, Rocha SD, Pagotto V, et al. Prevalence and risk factors for self-report diabetes mellitus: a population-based study. Int J Environ Res Public Health. 2020;17(18):6497.

Free radical research.

Zhu B, Qu S. The relationship between diabetes mellitus and cancers and its underlying mechanisms. Front Endocrinol. 2022;13:800995.

Mojarrad M, Moghbeli M. Genetic and molecular biology of bladder cancer among Iranian patients. Mol Genet Genomic Med. 2020;8(6):e1233.

Article   PubMed   PubMed Central   Google Scholar  

Moghbeli M. Genetic and molecular biology of breast cancer among Iranian patients. J Transl Med. 2019;17(1):218.

Abbaszadegan MR, Moghbeli M. Genetic and molecular origins of colorectal Cancer among the iranians: an update. Diagn Pathol. 2018;13(1):97.

Kim I. A brief overview of cell therapy and its product. J Korean Association Oral Maxillofacial Surg. 2013;39(5):201.

Mount NM, Ward SJ, Kefalas P, Hyllner J. Cell-based therapy technology classifications and translational challenges. Philosophical Trans Royal Soc B: Biol Sci. 2015;370(1680):20150017.

El-Kadiry AE-H, Rafei M, Shammaa R. Cell therapy: types, regulation, and clinical benefits. Front Med. 2021;8:756029.

Squifflet J-P, Gruessner R, Sutherland D. The history of pancreas transplantation: past, present and future. Acta Chir Belg. 2008;108(3):367–78.

Article   PubMed   Google Scholar  

Parums DV. First Regulatory approval for allogeneic pancreatic islet Beta cell infusion for adult patients with type 1 diabetes Mellitus. Med Sci Monitor: Int Med J Experimental Clin Res. 2023;29:e941918–1.

Yang L, Hu Z-M, Jiang F-X, Wang W. Stem cell therapy for insulin-dependent diabetes: are we still on the road? World J Stem Cells. 2022;14(7):503.

Affan M, Dar MS. Donislecel-the first approved pancreatic islet cell therapy medication for type 1 diabetes: a letter to the editor. Ir J Med Sci (1971-). 2023:1–2.

Harris E. FDA greenlights first cell therapy for adults with type 1 diabetes. JAMA. 2023.

Soon-Shiong P, Heintz R, Merideth N, Yao Q, Yao Z, Zheng T, et al. Insulin independence in a type 1 diabetic patient after encapsulated islet transplantation. Lancet (London England). 1994;343(8903):950–1.

Calafiore R, Basta G, Luca G, Lemmi A, Montanucci MP, Calabrese G, et al. Microencapsulated pancreatic islet allografts into nonimmunosuppressed patients with type 1 diabetes: first two cases. Diabetes Care. 2006;29(1):137–8.

Tuch BE, Keogh GW, Williams LJ, Wu W, Foster JL, Vaithilingam V, et al. Safety and viability of microencapsulated human islets transplanted into diabetic humans. Diabetes Care. 2009;32(10):1887–9.

Weng L, Wang X, Liu H, Yu Z, Liu S. Light-responsive microneedle array with tunable insulin release function for painless and on-demand anti-diabetic therapy. Mater Lett. 2023:135684.

Okcu A, Yazir Y, Şimşek T, Mert S, Duruksu G, Öztürk A, et al. Investigation of the effect of pancreatic decellularized matrix on encapsulated islets of Langerhans with mesenchymal stem cells. Tissue Cell. 2023;82:102110.

Khaliq T, Sohail M, Minhas MU, Mahmood A, Munir A, Qalawlus AHM, et al. Hyaluronic acid/alginate-based biomimetic hydrogel membranes for accelerated diabetic wound repair. Int J Pharm. 2023;643:123244.

Kuwabara R, Qin T, Llacua LA, Hu S, Boekschoten MV, de Haan BJ, et al. Extracellular matrix inclusion in immunoisolating alginate-based microcapsules promotes longevity, reduces fibrosis, and supports function of islet allografts in vivo. Acta Biomater. 2023;158:151–62.

Kirk K, Hao E, Lahmy R, Itkin-Ansari P. Human embryonic stem cell derived islet progenitors mature inside an encapsulation device without evidence of increased biomass or cell escape. Stem cell Res. 2014;12(3):807–14.

Dufrane D, van Steenberghe M, Goebbels R-M, Saliez A, Guiot Y, Gianello P. The influence of implantation site on the biocompatibility and survival of alginate encapsulated pig islets in rats. Biomaterials. 2006;27(17):3201–8.

Pullen LC. Stem cell–derived pancreatic progenitor cells have now been transplanted into patients: report from IPITA 2018. Wiley Online Library; 2018. pp. 1581–2.

Dang HP, Chen H, Dargaville TR, Tuch BE. Cell delivery systems: toward the next generation of cell therapies for type 1 diabetes. J Cell Mol Med. 2022;26(18):4756–67.

Viacyte. ViaCyte and gore enter clinical phase agreement based on novel membrane technology for PEC-encap product candidate. 2020.

Viacyte. viacyte announces initiation of phase 2 study of encapsulated cell therapy for type 1 diabetes patients 2021 2021. https://viacyte.com/press-releases/viacyte‐announces‐initiation‐of‐phase‐2‐study‐of‐encapsulated‐cell‐ther‐apy‐for‐type‐1‐diabetes‐patients/ .

Hodgson J. Drug pipeline 3Q23—ERT, bispecifics and CRISPR in sickle cell disease. Nat Biotechnol. 2023;41(11):1498–500.

Pagliuca F. Pre-clinical proof-of-Concept in two lead programs in type 1 diabetes. International Socety for Stem Cell Research; 2019.

Jones PM, Persaud SJ. β-cell replacement therapy for type 1 diabetes: closer and closer. Diabet Med. 2022;39(6).

Carlsson P-O, Espes D, Sedigh A, Rotem A, Zimerman B, Grinberg H, et al. Transplantation of macroencapsulated human islets within the bioartificial pancreas βAir to patients with type 1 diabetes mellitus. Am J Transplant. 2018;18(7):1735–44.

Ludwig B, Zimerman B, Steffen A, Yavriants K, Azarov D, Reichel A, et al. A novel device for islet transplantation providing immune protection and oxygen supply. Horm Metab Res. 2010;42(13):918–22.

Evron Y, Colton CK, Ludwig B, Weir GC, Zimermann B, Maimon S, et al. Long-term viability and function of transplanted islets macroencapsulated at high density are achieved by enhanced oxygen supply. Sci Rep. 2018;8(1):6508.

Cao R, Avgoustiniatos E, Papas K, de Vos P, Lakey JR. Mathematical predictions of oxygen availability in micro-and macro‐encapsulated human and porcine pancreatic islets. J Biomedical Mater Res Part B: Appl Biomaterials. 2020;108(2):343–52.

Gala-Lopez B, Pepper A, Dinyari P, Malcolm A, Kin T, Pawlick L, et al. Subcutaneous clinical islet transplantation in a prevascularized subcutaneous pouch–preliminary experience. CellR4. 2016;4(5):e2132.

Google Scholar  

Sernova Corp Presents Positive Preliminary. Safety and Efficacy Data in its Phase I/II Clinical Trial for Type-1 Diabetes: Biospace. https://www.biospace.com/article/sernova‐corp‐presents‐positive‐preliminary‐safety‐and‐efficacy‐data‐in‐its‐phase‐i‐ii‐clinical‐trial‐for‐type‐1‐diabetes/ .

Bachul PJ, Perez-Gutierrez A, Juengel B, Golab K, Basto L, Perea L et al. 306-OR: modified approach for improved isllotransplantation into prevascularized sernova cell pouch device: preliminary results of the phase i/ii clinical trial at University of Chicago. Diabetes. 2022;71(Supplement_1).

Vegas AJ, Veiseh O, Doloff JC, Ma M, Tam HH, Bratlie K, et al. Combinatorial hydrogel library enables identification of materials that mitigate the foreign body response in primates. Nat Biotechnol. 2016;34(3):345–52.

Vegas AJ, Veiseh O, Gürtler M, Millman JR, Pagliuca FW, Bader AR, et al. Long-term glycemic control using polymer-encapsulated human stem cell–derived beta cells in immune-competent mice. Nat Med. 2016;22(3):306–11.

Shapiro AD, Konkle BA, Croteau SE, Miesbach WA, Hay CRM, Kazmi R, et al. First-in-human phase 1/2 clinical trial of SIG-001, an innovative shielded cell therapy platform, for hemophilia Α. Blood. 2020;136:8.

Taraballi F, Sushnitha M, Tsao C, Bauza G, Liverani C, Shi A, et al. Biomimetic tissue engineering: tuning the immune and inflammatory response to implantable biomaterials. Adv Healthc Mater. 2018;7(17):1800490.

Yesilyurt V, Veiseh O, Doloff JC, Li J, Bose S, Xie X, et al. A facile and versatile method to endow biomaterial devices with zwitterionic surface coatings. Adv Healthc Mater. 2017;6(4):1601091.

Liu Q, Chiu A, Wang L-H, An D, Zhong M, Smink AM, et al. Zwitterionically modified alginates mitigate cellular overgrowth for cell encapsulation. Nat Commun. 2019;10(1):5262.

Noverraz F, Montanari E, Pimenta J, Szabó L, Ortiz D, Gonelle-Gispert C, et al. Antifibrotic effect of ketoprofen-grafted alginate microcapsules in the transplantation of insulin producing cells. Bioconjug Chem. 2018;29(6):1932–41.

Jeon SI, Jeong J-H, Kim JE, Haque MR, Kim J, Byun Y, et al. Synthesis of PEG-dendron for surface modification of pancreatic islets and suppression of the immune response. J Mater Chem B. 2021;9(11):2631–40.

Derakhshankhah H, Sajadimajd S, Jahanshahi F, Samsonchi Z, Karimi H, Hajizadeh-Saffar E, et al. Immunoengineering Biomaterials in Cell-based therapy for type 1 diabetes. Tissue Eng Part B: Reviews. 2022;28(5):1053–66.

Piemonti L, Maffi P, Nano R, Bertuzzi F, Melzi R, Mercalli A, et al. Treating diabetes with islet transplantation: lessons from the Milan experience. Transplantation, Bioengineering, and regeneration of the endocrine pancreas. Elsevier; 2020. pp. 645–58.

Azzi J, Tang L, Moore R, Tong R, El Haddad N, Akiyoshi T, et al. Polylactide-cyclosporin A nanoparticles for targeted immunosuppression. FASEB J. 2010;24(10):3927.

Chen X, Liu H, Li H, Cheng Y, Yang L, Liu Y. In vitro expansion and differentiation of rat pancreatic duct-derived stem cells into insulin secreting cells using a dynamic three-dimensional cell culture system. Genet Mol Res. 2016;15(2).

Becker MW, Simonovich JA, Phelps EA. Engineered microenvironments and microdevices for modeling the pathophysiology of type 1 diabetes. Biomaterials. 2019;198:49–62.

Graham JG, Zhang X, Goodman A, Pothoven K, Houlihan J, Wang S, et al. PLG scaffold delivered antigen-specific regulatory T cells induce systemic tolerance in autoimmune diabetes. Tissue Eng Part A. 2013;19(11–12):1465–75.

Izadi Z, Hajizadeh-Saffar E, Hadjati J, Habibi-Anbouhi M, Ghanian MH, Sadeghi-Abandansari H, et al. Tolerance induction by surface immobilization of Jagged-1 for immunoprotection of pancreatic islets. Biomaterials. 2018;182:191–201.

McHugh MD, Park J, Uhrich R, Gao W, Horwitz DA, Fahmy TM. Paracrine co-delivery of TGF-β and IL-2 using CD4-targeted nanoparticles for induction and maintenance of regulatory T cells. Biomaterials. 2015;59:172–81.

Chen H, Teramura Y, Iwata H. Co-immobilization of urokinase and thrombomodulin on islet surfaces by poly (ethylene glycol)-conjugated phospholipid. J Controlled Release. 2011;150(2):229–34.

Su J, Hu B-H, Lowe WL Jr, Kaufman DB, Messersmith PB. Anti-inflammatory peptide-functionalized hydrogels for insulin-secreting cell encapsulation. Biomaterials. 2010;31(2):308–14.

Dong H, Fahmy TM, Metcalfe SM, Morton SL, Dong X, Inverardi L, et al. Immuno-isolation of pancreatic islet allografts using pegylated nanotherapy leads to long-term normoglycemia in full MHC mismatch recipient mice. PLoS ONE. 2012;7(12):e50265.

Kumar M, Nandi SK, Kaplan DL, Mandal BB. Localized immunomodulatory silk macrocapsules for islet-like spheroid formation and sustained insulin production. ACS Biomaterials Sci Eng. 2017;3(10):2443–56.

Hotaling NA, Tang L, Irvine DJ, Babensee JE. Biomaterial Strategies for Immunomodulation. Annu Rev Biomed Eng. 2015;17:317–49.

Shi Y, Zhao YZ, Jiang Z, Wang Z, Wang Q, Kou L, et al. Immune-Protective formulations and process strategies for improved survival and function of transplanted islets. Front Immunol. 2022;13:923241.

Zhang S, Yang H, Wang M, Mantovani D, Yang K, Witte F, et al. Immunomodulatory biomaterials against bacterial infections: Progress, challenges, and future perspectives. Innovation. 2023;4(6):100503.

CAS   PubMed   PubMed Central   Google Scholar  

Accolla RP, Simmons AM, Stabler CL. Integrating Additive Manufacturing techniques to improve cell-based implants for the treatment of type 1 diabetes. Adv Healthc Mater. 2022;11(13):e2200243.

Gross BC, Erkal JL, Lockwood SY, Chen C, Spence DM. Evaluation of 3D printing and its potential impact on biotechnology and the chemical sciences. ACS; 2014.

Bol RJ, Šavija B. Micromechanical models for FDM 3D-Printed polymers: a review. Polymers. 2023;15(23):4497.

Paul S. Finite element analysis in fused deposition modeling research: a literature review. Measurement. 2021;178:109320.

Monaldo E, Ricci M, Marfia S. Mechanical properties of 3D printed polylactic acid elements: experimental and numerical insights. Mech Mater. 2023;177:104551.

Anoop M, Senthil P. Microscale representative volume element based numerical analysis on mechanical properties of fused deposition modelling components. Materials Today: Proceedings. 2021;39:563 – 71.

McGuigan AP, Sefton MV. Vascularized organoid engineered by modular assembly enables blood perfusion. Proceedings of the National Academy of Sciences. 2006;103(31):11461-6.

Pedraza E, Coronel MM, Fraker CA, Ricordi C, Stabler CL. Preventing hypoxia-induced cell death in beta cells and islets via hydrolytically activated, oxygen-generating biomaterials. Proceedings of the National Academy of Sciences. 2012;109(11):4245-50.

Espona-Noguera A, Ciriza J, Cañibano-Hernández A, Orive G, Hernández RM, del Saenz L, et al. Review of advanced hydrogel-based cell encapsulation systems for insulin delivery in type 1 diabetes mellitus. Pharmaceutics. 2019;11(11):597.

Dimitrioglou N, Kanelli M, Papageorgiou E, Karatzas T, Hatziavramidis D. Paving the way for successful islet encapsulation. Drug Discovery Today. 2019;24(3):737–48.

Omer A, Duvivier-Kali V, Fernandes J, Tchipashvili V, Colton CK, Weir GC. Long-term normoglycemia in rats receiving transplants with encapsulated islets. Transplantation. 2005;79(1):52–8.

Song S, Roy S. Progress and challenges in macroencapsulation approaches for type 1 diabetes (T1D) treatment: cells, biomaterials, and devices. Biotechnol Bioeng. 2016;113(7):1381–402.

Zhi ZL, Kerby A, King AJF, Jones PM, Pickup JC. Nano-scale encapsulation enhances allograft survival and function of islets transplanted in a mouse model of diabetes. Diabetologia. 2012;55(4):1081–90.

Farina M, Chua CYX, Ballerini A, Thekkedath U, Alexander JF, Rhudy JR, et al. Transcutaneously refillable, 3D-printed biopolymeric encapsulation system for the transplantation of endocrine cells. Biomaterials. 2018;177:125–38.

Farina M, Ballerini A, Fraga DW, Nicolov E, Hogan M, Demarchi D et al. 3D printed vascularized device for Subcutaneous Transplantation of Human islets. Biotechnol J. 2017;12(9).

Lei D, Yang Y, Liu Z, Yang B, Gong W, Chen S, et al. 3D printing of biomimetic vasculature for tissue regeneration. Mater Horiz. 2019;6(6):1197–206.

Melchels FP, Domingos MA, Klein TJ, Malda J, Bartolo PJ, Hutmacher DW. Additive manufacturing of tissues and organs. Prog Polym Sci. 2012;37(8):1079–104.

Ernst AU, Wang LH, Ma M. Interconnected toroidal hydrogels for islet encapsulation. Adv Healthc Mater. 2019;8(12):1900423.

Liang J-P, Accolla RP, Jiang K, Li Y, Stabler CL. Controlled release of anti-inflammatory and proangiogenic factors from macroporous scaffolds. Tissue Eng Part A. 2021;27(19–20):1275–89.

Pedraza E, Brady A-C, Fraker CA, Molano RD, Sukert S, Berman DM, et al. Macroporous three-dimensional PDMS scaffolds for extrahepatic islet transplantation. Cell Transplant. 2013;22(7):1123–35.

Chiu Y-C, Cheng M-H, Engel H, Kao S-W, Larson JC, Gupta S, et al. The role of pore size on vascularization and tissue remodeling in PEG hydrogels. Biomaterials. 2011;32(26):6045–51.

Kuss MA, Wu S, Wang Y, Untrauer JB, Li W, Lim JY, et al. Prevascularization of 3D printed bone scaffolds by bioactive hydrogels and cell co-culture. J Biomedical Mater Res Part B: Appl Biomaterials. 2018;106(5):1788–98.

Liu X, Jakus AE, Kural M, Qian H, Engler A, Ghaedi M, et al. Vascularization of natural and synthetic bone scaffolds. Cell Transplant. 2018;27(8):1269–80.

Costa-Almeida R, Gomez-Lazaro M, Ramalho C, Granja PL, Soares R, Guerreiro SG. Fibroblast-endothelial partners for vascularization strategies in tissue engineering. Tissue Eng Part A. 2015;21(5–6):1055–65.

Newman AC, Nakatsu MN, Chou W, Gershon PD, Hughes CC. The requirement for fibroblasts in angiogenesis: fibroblast-derived matrix proteins are essential for endothelial cell lumen formation. Mol Biol Cell. 2011;22(20):3791–800.

Vlahos AE, Cober N, Sefton MV. Modular tissue engineering for the vascularization of subcutaneously transplanted pancreatic islets. Proceedings of the National Academy of Sciences. 2017;114(35):9337-42.

Farina M, Ballerini A, Fraga DW, Nicolov E, Hogan M, Demarchi D, et al. 3D printed vascularized device for subcutaneous transplantation of human islets. Biotechnol J. 2017;12(9):1700169.

Bertassoni LE, Cecconi M, Manoharan V, Nikkhah M, Hjortnaes J, Cristino AL, et al. Hydrogel bioprinted microchannel networks for vascularization of tissue engineering constructs. Lab Chip. 2014;14(13):2202–11.

Jia W, Gungor-Ozkerim PS, Zhang YS, Yue K, Zhu K, Liu W, et al. Direct 3D bioprinting of perfusable vascular constructs using a blend bioink. Biomaterials. 2016;106:58–68.

Gao Q, Liu Z, Lin Z, Qiu J, Liu Y, Liu A, et al. 3D bioprinting of vessel-like structures with multilevel fluidic channels. ACS Biomaterials Sci Eng. 2017;3(3):399–408.

Noor N, Shapira A, Edri R, Gal I, Wertheim L, Dvir T. 3D printing of personalized thick and perfusable cardiac patches and hearts. Adv Sci. 2019;6(11):1900344.

Hospodiuk M, Dey M, Ayan B, Sosnoski D, Moncal KK, Wu Y, et al. Sprouting angiogenesis in engineered pseudo islets. Biofabrication. 2018;10(3):035003.

Marchioli G, Luca AD, de Koning E, Engelse M, Van Blitterswijk CA, Karperien M, et al. Hybrid polycaprolactone/alginate scaffolds functionalized with VEGF to promote de novo vessel formation for the transplantation of islets of Langerhans. Adv Healthc Mater. 2016;5(13):1606–16.

Dionne KE, Colton CK, Lyarmush M. Effect of hypoxia on insulin secretion by isolated rat and canine islets of Langerhans. Diabetes. 1993;42(1):12–21.

de Groot M, Schuurs TA, Keizer PP, Fekken S, Leuvenink HG, Van Schilfgaarde R. Response of encapsulated rat pancreatic islets to hypoxia. Cell Transplant. 2003;12(8):867–75.

Thomas F, Wu J, Contreras JL, Smyth C, Bilbao G, He J, et al. A tripartite anoikis-like mechanism causes early isolated islet apoptosis. Surgery. 2001;130(2):333–8.

Barkai U, Rotem A, de Vos P. Survival of encapsulated islets: more than a membrane story. World J Transplantation. 2016;6(1):69.

Jiang K, Chaimov D, Patel SN, Liang JP, Wiggins SC, Samojlik MM, et al. 3-D physiomimetic extracellular matrix hydrogels provide a supportive microenvironment for rodent and human islet culture. Biomaterials. 2019;198:37–48.

Pati F, Jang J, Ha D, Won Kim S, Rhie J, Shim J, et al. Printing three-dimensional tissue analogues with decellularized extracellular matrix bioink. Nat Commun. 2014;5:3935.

Kim BS, Kwon YW, Kong J-S, Park GT, Gao G, Han W, et al. 3D cell printing of in vitro stabilized skin model and in vivo pre-vascularized skin patch using tissue-specific extracellular matrix bioink: a step towards advanced skin tissue engineering. Biomaterials. 2018;168:38–53.

Hu S, Martinez-Garcia FD, Moeun BN, Burgess JK, Harmsen MC, Hoesli C, et al. An immune regulatory 3D-printed alginate-pectin construct for immunoisolation of insulin producing β-cells. Mater Sci Engineering: C. 2021;123:112009.

Phelps EA, Templeman KL, Thulé PM, García AJ. Engineered VEGF-releasing PEG–MAL hydrogel for pancreatic islet vascularization. Drug Delivery Translational Res. 2015;5:125–36.

Kooptiwut S, Kaewin S, Semprasert N, Sujjitjoon J, Junking M, Suksri K, et al. Estradiol prevents high glucose-induced β-cell apoptosis by decreased BTG2 expression. Sci Rep. 2018;8(1):12256.

Dang TT, Thai AV, Cohen J, Slosberg JE, Siniakowicz K, Doloff JC, et al. Enhanced function of immuno-isolated islets in diabetes therapy by co-encapsulation with an anti-inflammatory drug. Biomaterials. 2013;34(23):5792–801.

Wang Y, He D, Ni C, Zhou H, Wu S, Xue Z, et al. Vitamin D induces autophagy of pancreatic β-cells and enhances insulin secretion. Mol Med Rep. 2016;14(3):2644–50.

Tarafder S, Koch A, Jun Y, Chou C, Awadallah MR, Lee CH. Micro-precise spatiotemporal delivery system embedded in 3D printing for complex tissue regeneration. Biofabrication. 2016;8(2):025003.

Liu YY, Yu HC, Liu Y, Liang G, Zhang T, Hu QX. Dual drug spatiotemporal release from functional gradient scaffolds prepared using 3 D bioprinting and electrospinning. Polym Eng Sci. 2016;56(2):170–7.

Freeman FE, Pitacco P, van Dommelen LH, Nulty J, Browe DC, Shin J-Y, et al. 3D bioprinting spatiotemporally defined patterns of growth factors to tightly control tissue regeneration. Sci Adv. 2020;6(33):eabb5093.

Wong MS, Hawthorne WJ, Manolios N. Gene therapy in diabetes. Self Nonself. 2010;1(3):165.

Ahmad Z, Rasouli M, Azman AZF, Omar AR. Evaluation of insulin expression and secretion in genetically engineered gut K and L-cells. BMC Biotechnol. 2012;12:1–9.

Tudurí E, Bruin JE, Kieffer TJ. Restoring insulin production for type 1 diabetes. J Diabetes. 2012;4(4):319–31.

Romer AI, Sussel L. Pancreatic islet cell development and regeneration. Current opinion in endocrinology, diabetes, and obesity. 2015;22(4):255.

Jaén ML, Vilà L, Elias I, Jimenez V, Rodó J, Maggioni L, et al. Long-term efficacy and safety of insulin and glucokinase gene therapy for diabetes: 8-year follow-up in dogs. Mol therapy-methods Clin Dev. 2017;6:1–7.

Li H, Li X, Lam KS, Tam S, Xiao W, Xu R. Adeno-associated virus-mediated pancreatic and duodenal homeobox gene-1 expression enhanced differentiation of hepatic oval stem cells to insulin-producing cells in diabetic rats. J Biomed Sci. 2008;15:487–97.

Schwitzgebel VM, Scheel DW, Conners JR, Kalamaras J, Lee JE, Anderson DJ, et al. Expression of neurogenin3 reveals an islet cell precursor population in the pancreas. Development. 2000;127(16):3533–42.

Abed A, Critchlow C, Flatt PR, McClenaghan NH, Kelly C. Directed differentiation of progenitor cells towards an islet-cell phenotype. Am J Stem Cells. 2012;1(3):196.

PubMed   PubMed Central   Google Scholar  

Zhao M, Amiel SA, Ajami S, Jiang J, Rela M, Heaton N, et al. Amelioration of streptozotocin-induced diabetes in mice with cells derived from human marrow stromal cells. PLoS ONE. 2008;3(7):e2666.

Handorf AM, Sollinger HW, Alam T. Genetic engineering of surrogate β cells for treatment of type 1 diabetes mellitus. J Diabetes Mellitus. 2015;5(04):295–312.

Grant MB, Adu-Agyeiwaah Y, Vieira CP, Asare-Bediako B, Hammer SS, Calzi SL, et al. Intravitreal administration of AAV2-SIRT1 reverses diabetic retinopathy (DR) in a murine model of type 2 diabetes (T2D). Investig Ophthalmol Vis Sci. 2022;63(7):2310.

Yoon J-W, Jun H-S. Recent advances in insulin gene therapy for type 1 diabetes. Trends Mol Med. 2002;8(2):62–8.

Hou W-R, Xie S-N, Wang H-J, Su Y-Y, Lu J-L, Li L-L, et al. Intramuscular delivery of a naked DNA plasmid encoding proinsulin and pancreatic regenerating III protein ameliorates type 1 diabetes mellitus. Pharmacol Res. 2011;63(4):320–7.

Joo WS, Jeong JH, Nam K, Blevins KS, Salama ME, Kim SW. Polymeric delivery of therapeutic RAE-1 plasmid to the pancreatic islets for the prevention of type 1 diabetes. J Controlled Release. 2012;162(3):606–11.

Dezashibi HM, Shabani A. A Mini-review of Current Treatment approaches and Gene Therapy as potential interventions for diabetes Mellitus types 1. Adv Biomed Res. 2023;12:219.

Vantyghem M-C, de Koning EJ, Pattou F, Rickels MR. Advances in β-cell replacement therapy for the treatment of type 1 diabetes. Lancet. 2019;394(10205):1274–85.

Hudson A, Bradbury L, Johnson R, Fuggle S, Shaw J, Casey J, et al. The UK pancreas allocation scheme for whole organ and islet transplantation. Am J Transplant. 2015;15(9):2443–55.

Cornateanu SM, O’Neill S, Dholakia S, Counter CJ, Sherif AE, Casey JJ, et al. Pancreas utilization rates in the UK–an 11-year analysis. Transpl Int. 2021;34(7):1306–18.

Nordheim E, Lindahl JP, Carlsen RK, Åsberg A, Birkeland KI, Horneland R, et al. Patient selection for islet or solid organ pancreas transplantation: experiences from a multidisciplinary outpatient-clinic approach. Endocr Connections. 2021;10(2):230–9.

Arifin DR, Bulte JW. In vivo imaging of pancreatic islet grafts in diabetes treatment. Front Endocrinol. 2021;12:640117.

Murakami T, Fujimoto H, Inagaki N. Non-invasive beta-cell imaging: visualization, quantification, and beyond. Front Endocrinol. 2021;12:714348.

Piemonti L, Everly MJ, Maffi P, Scavini M, Poli F, Nano R, et al. Alloantibody and autoantibody monitoring predicts islet transplantation outcome in human type 1 diabetes. Diabetes. 2013;62(5):1656–64.

Anteby R, Lucander A, Bachul PJ, Pyda J, Grybowski D, Basto L, et al. Evaluating the prognostic value of islet autoantibody monitoring in islet transplant recipients with long-standing type 1 diabetes mellitus. J Clin Med. 2021;10(12):2708.

Buron F, Reffet S, Badet L, Morelon E, Thaunat O. Immunological monitoring in beta cell replacement: towards a pathophysiology-guided implementation of biomarkers. Curr Diab Rep. 2021;21:1–11.

Cantarelli E, Piemonti L. Alternative transplantation sites for pancreatic islet grafts. Curr Diab Rep. 2011;11:364–74.

Tremmel DM, Odorico JS. Rebuilding a better home for transplanted islets. Organogenesis. 2018;14(4):163–8.

Citro A, Moser PT, Dugnani E, Rajab TK, Ren X, Evangelista-Leite D, et al. Biofabrication of a vascularized islet organ for type 1 diabetes. Biomaterials. 2019;199:40–51.

Basta G, Montanucci P, Calafiore R. Microencapsulation of cells and molecular therapy of type 1 diabetes mellitus: the actual state and future perspectives between promise and progress. J Diabetes Invest. 2021;12(3):301–9.

Samojlik MM, Stabler CL. Designing biomaterials for the modulation of allogeneic and autoimmune responses to cellular implants in type 1 diabetes. Acta Biomater. 2021;133:87–101.

Carlsson P-O, Schwarcz E, Korsgren O, Le Blanc K. Preserved β-cell function in type 1 diabetes by mesenchymal stromal cells. Diabetes. 2015;64(2):587–92.

Madani S, Setudeh A, Aghayan HR, Alavi-Moghadam S, Rouhifard M, Rezaei N, et al. Placenta derived mesenchymal stem cells transplantation in type 1 diabetes: preliminary report of phase 1 clinical trial. J Diabetes Metabolic Disorders. 2021;20:1179–89.

Pagliuca FW, Millman JR, Gürtler M, Segel M, Van Dervort A, Ryu JH, et al. Generation of functional human pancreatic β cells in vitro. Cell. 2014;159(2):428–39.

Russ HA, Parent AV, Ringler JJ, Hennings TG, Nair GG, Shveygert M, et al. Controlled induction of human pancreatic progenitors produces functional beta-like cells in vitro. EMBO J. 2015;34(13):1759–72.

Sambathkumar R, Migliorini A, Nostro MC. Pluripotent stem cell-derived pancreatic progenitors and β-like cells for type 1 diabetes treatment. Physiology. 2018;33(6):394–402.

Sordi V, Monaco L, Piemonti L. Cell therapy for type 1 diabetes: from islet transplantation to stem cells. Hormone Res Paediatrics. 2022;96(6):658–69.

Henry RR, Pettus J, Wilensky J, SHAPIRO AJ, Senior PA, Roep B et al. Initial clinical evaluation of VC-01TM combination product—a stem cell–derived islet replacement for type 1 diabetes (T1D). Diabetes. 2018;67(Supplement_1).

Shapiro A, Thompson D, Donner TW, Bellin MD, Hsueh W, Pettus JH et al. Insulin expression and glucose-responsive circulating C-peptide in type 1 diabetes patients implanted subcutaneously with pluripotent stem cell-derived pancreatic endoderm cells in a macro-device. David and Donner, Thomas W and Bellin, Melena D and Hsueh, Willa and Pettus, Jeremy H and Wilensky, Jon S and Daniels, Mark and Wang, Richard M and Kroon, Evert J and Brandon, Eugene Paul and D’Amour, Kevin A and Foyt, Howard, Insulin Expression and Glucose-Responsive Circulating C-Peptide in Type. 2019;1.

Keymeulen B, Jacobs-Tulleneers-Thevissen D, Kroon EJ, Jaiman MS, Daniels M, Wang R et al. 196-LB: stem cell–derived islet replacement therapy (VC-02) demonstrates production of C-peptide in patients with type 1 diabetes (T1D) and hypoglycemia unawareness. Diabetes. 2021;70(Supplement_1).

Piemonti L. Felix dies natalis, insulin… ceterum autem censeo beta is better. Acta Diabetol. 2021;58(10):1287–306.

Sordi V, Pellegrini S, Piemonti L. Immunological issues after stem cell-based β cell replacement. Curr Diab Rep. 2017;17:1–8.

Coe TM, Markmann JF, Rickert CG. Current status of porcine islet xenotransplantation. Curr Opin Organ Transpl. 2020;25(5):449–56.

Edgar L, Pu T, Porter B, Aziz J, La Pointe C, Asthana A, et al. Regenerative medicine, organ bioengineering and transplantation. J Br Surg. 2020;107(7):793–800.

Mathur A, Taurin S, Alshammary S. The safety and efficacy of mesenchymal stem cells in the treatment of type 2 Diabetes- A literature review. Diabetes Metab Syndr Obes. 2023;16:769–77.

Hogrebe NJ, Ishahak M, Millman JR. Developments in stem cell-derived islet replacement therapy for treating type 1 diabetes. Cell Stem Cell. 2023;30(5):530–48.

Paraskevas S, Maysinger D, Wang R, Duguid WP, Rosenberg L. Cell loss in isolated human islets occurs by apoptosis. Pancreas. 2000;20(3):270–6.

Kelly OG, Chan MY, Martinson LA, Kadoya K, Ostertag TM, Ross KG, et al. Cell-surface markers for the isolation of pancreatic cell types derived from human embryonic stem cells. Nat Biotechnol. 2011;29(8):750–6.

Rezania A, Bruin JE, Riedel MJ, Mojibian M, Asadi A, Xu J, et al. Maturation of human embryonic stem cell–derived pancreatic progenitors into functional islets capable of treating pre-existing diabetes in mice. Diabetes. 2012;61(8):2016–29.

Kroon E, Martinson LA, Kadoya K, Bang AG, Kelly OG, Eliazer S, et al. Pancreatic endoderm derived from human embryonic stem cells generates glucose-responsive insulin-secreting cells in vivo. Nat Biotechnol. 2008;26(4):443–52.

Agulnick AD, Ambruzs DM, Moorman MA, Bhoumik A, Cesario RM, Payne JK, et al. Insulin-producing endocrine cells differentiated in vitro from human embryonic stem cells function in macroencapsulation devices in vivo. Stem Cells Translational Med. 2015;4(10):1214–22.

Ramzy A, Thompson DM, Ward-Hartstonge KA, Ivison S, Cook L, Garcia RV, et al. Implanted pluripotent stem-cell-derived pancreatic endoderm cells secrete glucose-responsive C-peptide in patients with type 1 diabetes. Cell Stem Cell. 2021;28(12):2047–61. e5.

Dolgin E, Diabetes. Encapsulating the problem. Nature. 2016;540(7632):S60–2.

Rezania A, Bruin JE, Arora P, Rubin A, Batushansky I, Asadi A, et al. Reversal of diabetes with insulin-producing cells derived in vitro from human pluripotent stem cells. Nat Biotechnol. 2014;32(11):1121–33.

Hogrebe NJ, Augsornworawat P, Maxwell KG, Velazco-Cruz L, Millman JR. Targeting the cytoskeleton to direct pancreatic differentiation of human pluripotent stem cells. Nat Biotechnol. 2020;38(4):460–70.

Nair GG, Liu JS, Russ HA, Tran S, Saxton MS, Chen R, et al. Recapitulating endocrine cell clustering in culture promotes maturation of human stem-cell-derived β cells. Nat Cell Biol. 2019;21(2):263–74.

Shapiro AJ, Thompson D, Donner TW, Bellin MD, Hsueh W, Pettus J et al. Insulin expression and C-peptide in type 1 diabetes subjects implanted with stem cell-derived pancreatic endoderm cells in an encapsulation device. Cell Rep Med. 2021;2(12).

Witkowski P, Anteby R, Olaitan OK, Forbes RC, Niederhaus S, Ricordi C, et al. Pancreatic islets Quality and Potency cannot be verified as required for drugs: reflection on the FDA Review of a biological license application for human islets. Transplantation. 2021;105(12):e409–10.

Download references

Acknowledgements

Author information, authors and affiliations.

Noncommunicable Diseases Research Center, Neyshabur University of Medical Sciences, Neyshabur, Iran

Ramin Raoufinia

Department of Medical Genetics and Molecular Medicine, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

Ramin Raoufinia, Hamid Reza Rahimi, Ehsan Saburi & Meysam Moghbeli

You can also search for this author in PubMed   Google Scholar

Contributions

RR, HRR, and ES were involved in search strategy and drafting. MM revised, designed, and supervised the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Meysam Moghbeli .

Ethics declarations

Ethics approval and consent to participate.

Not applicable.

Consent for publication

Competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Raoufinia, R., Rahimi, H.R., Saburi, E. et al. Advances and challenges of the cell-based therapies among diabetic patients. J Transl Med 22 , 435 (2024). https://doi.org/10.1186/s12967-024-05226-3

Download citation

Received : 14 February 2024

Accepted : 22 April 2024

Published : 08 May 2024

DOI : https://doi.org/10.1186/s12967-024-05226-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Cell therapy
• Translplantation
• Immunosuppression

Journal of Translational Medicine

ISSN: 1479-5876

• Submission enquiries: Access here and click Contact Us
• General enquiries: [email protected]