Introduction

Diabetes mellitus (DM) is a widely prevalent non-communicable disease characterized by hyperglycemia, affecting populations globally with increasing prevalence1,2. Type 2 diabetes mellitus (T2DM) is the most common subtype, distinguished from type 1 diabetes (T1DM) by factors such as age at onset, insulin resistance, and varying need for insulin therapy3,4. Projections indicate a significant rise in global diabetes cases, particularly in developing countries like those in Africa, where urbanization and lifestyle changes contribute to its occurrence5,6. By 2030, the World Health Organization (WHO) estimates more than half a million people will have diabetes worldwide, with substantial implications for public health and national economies, particularly in low-resource settings7,8,9.

T2DM is linked with disabling and potentially fatal microvascular and macrovascular complications10,11. Microvascular complications, which affect small blood vessels, are major contributors to end-stage renal disease, various painful neuropathies, and blindness12. Due to genetic predisposition and chronic hyperglycemia, the microvasculature in diabetics is particularly vulnerable to damage in vital organs such as the kidneys, eyes, and nervous system. Diabetic nephropathy is the most common cause of severe renal disease, diabetic retinopathy is a leading cause of blindness in the diabetic population, and diabetic neuropathy is the primary contributing factor to diabetic foot ulcers and amputations13,14.

The prevalence of microvascular complications ranged from 18.0 to 57.5% in Asia15,16, from 34.3 to 48.4% in the Middle East17,18,19, Ghana 35.3%20and 47.8% in Nigeria21. The increase in the prevalence of DM and its complications has also been noted in Ethiopia, with the prevalence of diabetic complications ranging from 20.4–61%22,23,24,25,26. The lowest reported rate of microvascular complications of T2DM was from Gondar25while the highest rate was reported from the Gurage Zone at 61%23.

Previous studies have shown that factors like age, sex, duration of diabetes, history of hypertension, triglycerides, hypercholesterolemia, dyslipidemia, poor glycemic control, physical inactivity, and positive proteinuria all influence the development of diabetic microvascular complications in T2DM patients14,27,28,29,30,31,32.

Early detection and effective treatment of diabetic microvascular complications are critical for improving patient outcomes and reducing healthcare costs33,34,35. These complications significantly impact morbidity and mortality associated with diabetes globally, placing substantial economic burdens on healthcare systems36,37. Timely interventions not only prolong life expectancy and enhance quality of life but also mitigate the need for costly treatments and hospitalizations. However, there is a dearth of evidence particularly within the study area, to demonstrate the prevalence and factors associated with diabetic microvascular complications. Our study aimed to provide insights into diabetic microvascular complications within our local context, aiming to guide targeted interventions, enhance patient care, and contribute valuable perspectives to the broader discourse on effective diabetes management. Thus, this study aimed to determine the prevalence and associated factors of diabetic microvascular complications among adults with T2DM in Adama, central Ethiopia.

Methods

Study design, setting, and population

An institutional-based cross-sectional study was conducted at Adama Hospital Medical College (AHMC) in Ethiopia, covering a period of ten years from January 2012 to December 2022. AHMC is located in Adama town, approximately 99 km southeast of Addis Ababa in the Great Rift Valley of East Africa. It is one of the largest public teaching hospitals in the Oromia region, serving a catchment area of over five million people and acting as a referral hub for surrounding zones and regions. All adult T2DM patients who were on follow-up at AHMC constituted the source population, while all newly diagnosed adult T2DM patients who were on follow-up at AHMC from January 2012 to December 2022 were considered the study population.

Sample size determination and sampling procedure

The sample size was determined using a formula tailored for estimating a single population proportion. The calculation was based on specific statistical assumptions, including:

  • A cross-sectional study design to achieve the study objective.

  • A prevalence of DM microvascular complications (P) of 33.2%, derived from a previous study on DM microvascular complications38.

  • A confidence level of 95%, corresponding to a standard value (Z) of 1.96 and.

  • A calculated margin of error (d) of 0.048.

Thus, by inserting these parameters into the formula:

$$\text{n}=\frac{{(\text{z}\:{\alpha\:}/2)}^{2}\text{*}\text{p}\left(1-\text{p}\right)}{{\text{d}}^{2}}=\:\frac{{\left(1.96\right)}^{2}\text{*}0.332\left(1-0.332\right)}{{\left(0.048\right)}^{2}}=370$$

Finally, after adding a 5% adjustment for incomplete data, the final sample size for the study becomes 389.

The study participants were identified using their medical record numbers from individuals who had been under follow-up between January 2012 and December 2022, forming the initial sampling frame. From this group, participants were selected by a simple random sampling technique using computer-generated random numbers. This method ensured that each eligible individual had an equal opportunity to be included, minimizing potential biases and ensuring the sample’s representativeness of the broader population under study.

Study variables

Outcome variable

Microvascular complications (yes/no).

Independent variables

Socio-demographic variables (age, sex, place of residence, marital status), Clinical and comorbidity-related characteristics (type of treatment, proteinuria, triglyceride, total cholesterol, high-density lipoprotein, low-density lipoprotein, glycemic control, family history of T2DM, duration of DM, history of smoking, history of chronic heart disease, history of chronic kidney disease, history of stroke, history of hypertension).

Operational definitions

Microvascular complications

The presence of at least one of the following conditions associated with diabetes: diabetic neuropathy, diabetic nephropathy, or diabetic retinopathy, documented in the patient’s hospital record14,31,39.

Glycemic control

Hemoglobin A1C (HgA1C) below 7%, or the last fasting blood sugar (FBS) level 130 mg/dl or lower in the absence of documented HgA1C determined in less than three months, was considered as good glycemic control. Otherwise, it was classified as poor glycemic control40.

Data collection procedure and quality control

Data were gathered using a structured and pretested data extraction checklist developed after a comprehensive review of patient medical records, follow-up cards, diabetes registration logs, electronic information databases, and relevant prior studies. The checklist encompassed socio-demographic, clinical, and comorbidity-related characteristics. The data collection process was conducted by three trained nurses under the supervision of two public health professionals.

All data collectors and supervisors received one day of training focused on the study objectives, record retrieval procedures, and the overall data collection process. A pretest using 5% of the sample size (n = 19) was performed on records predating January 2012. Based on the pretest results, adjustments and corrections were made to the data extraction checklist. Throughout the data collection phase, supervisors and the principal investigator closely monitored the completeness and consistency of the data. In addition, all gathered data underwent thorough cross-checking during data entry to address any missing information.

Data processing and statistical analysis

The collected data were entered into Epi-Info version 7.2 software, and then exported to Statistical Package for the Social Sciences (SPSS) version 27 for processing and analysis. Before commencing analysis, data processing operations including data cleaning, computing, transforming, coding, recoding, and variable grouping were performed. Descriptive statistics were used to examine and summarize the characteristics of the study population across all variables. Frequency distributions were calculated for categorical variables, while appropriate numerical summary measures were employed to summarize continuous variables after checking for data normality using the Shapiro-Wilk test. The prevalence of diabetic microvascular complications was estimated using proportions and a 95% confidence interval (CI).

To model the association between diabetic microvascular complications and explanatory variables, binary logistic regression was employed. Hence, a bivariable logistic regression model was fitted to assess the crude associations between diabetic microvascular complications and each explanatory variable. At this stage, a p-value of 0.25 was chosen as the cut-off to select variables for multivariable logistic regression analysis, in which the associations were adjusted for potential confounders. Then all candidate variables were included in the multivariable regression analysis to pinpoint factors significantly associated with diabetic microvascular complications. A standard model-building approach was used to develop the model.

Before examining the association between diabetic microvascular complications and the independent variables, the model’s suitability was assessed using diagnostic tests. Specifically, Hosmer and Lemeshow’s test was conducted to evaluate the model’s goodness of fit. The diagnostic results indicated the model fit the data well (p = 0.252). To assess the proportion of variation in diabetic microvascular complications accounted for by the combined influence of explanatory variables, Nagelkerke R-square was calculated. The findings indicated that 15.9% of the variation in diabetic microvascular complications is explained by the collective effects of the variables included in the model. Multicollinearity among the explanatory variables was examined using the variance inflation factor (VIF), which was found to be in the range of 1.015 to 1.269, indicating no collinearity among the covariates. In the final model, an adjusted odds ratio (AOR) with a 95% CI was used to estimate the strength of association, and statistical significance was proclaimed at a p-value < 0.05.

Results

Socio-demographic characteristics

A total of 381 records of patients with T2DM were reviewed and included in the final analysis. The median age of the participants was 49 years (IQR = 38–60). Among the participants, 208 (54.6%) were male. The majority, 281 (73.8%), resided in Adama, and 283 (74.3%) were married (Table 1).

Table 1 Sociodemographic characteristics of patients with type 2 diabetes in Adama, central Ethiopia, 2023 (n = 381).
Full size table

Clinical and comorbidity-related characteristics

In this study, 172 participants (45.1%) were on oral hypoglycemic agents, while 343 (90%) had HDL levels under 40 mg/dL. The majority of DM patients, 331 (86.9%), had good glycemic control, 248 (63.8%) had been living with DM for less than 5 years, and 161 (42.3%) had a history of hypertension (Table 2).

Table 2 Clinical and comorbidity-related characteristics of patients with type 2 diabetes in Adama, central Ethiopia, 2023 (n = 381).
Full size table

The prevalence of diabetic microvascular complications

The overall prevalence of diabetic microvascular complications among T2DM patients was 21.8% (95% CI: 17.8–25.6). Among these complications, diabetic neuropathy was the most common at 16.8% (95% CI: 13.5–21.5), followed by diabetic retinopathy at 4.2% (95% CI: 2.4–6.3), and diabetic nephropathy at 2.9% (95% CI: 1.2–4.7). Additionally, 19.7% of the participants had only one microvascular complication, while 2.1% had more than one complication.

Factors associated with diabetic microvascular complications

In the bivariable logistic regression analysis, age, type of treatment, high-density lipoprotein level, glycemic control, family history of T2DM, duration of DM, and history of hypertension were found to have a crude association with diabetic microvascular complications at a p-value of < 0.25. After adjusting for all potential confounders in a multivariable logistic regression analysis, age, glycemic control, and history of hypertension remained statistically significant factors, each with a p-value of less than 0.05.

Consequently, this study found that T2DM patients aged 41–60 had 65% lower odds of developing diabetic microvascular complications compared to those aged over 60 years (AOR = 0.35, 95% CI: 0.18–0.68). The odds of developing diabetic microvascular complications were two-fold greater among T2DM patients with poor glycemic control compared to those with good glycemic control (AOR = 2.00, 95% CI: 1.01–3.98). Similarly, in contrast to T2DM patients without a history of hypertension, those with a history of hypertension exhibited 2.4 times higher odds of developing diabetic microvascular complications (AOR = 2.36, 95% CI: 1.39–4.00) (Table 3).

Table 3 Factors associated with diabetic microvascular complication among patients with type 2 diabetes in Adama, central Ethiopia, 2023 (n = 381).
Full size table

Discussion

This study revealed that the prevalence of diabetic microvascular complications was 21.8% (95% CI: 17.8–25.6). This is comparable to findings from studies conducted in Northern Ethiopia (19.5%)41and India (18.04%)28. Conversely, the prevalence found in this study is lower than that reported in studies from Northwest Ethiopia (26.3%)42, Southern Ethiopia (26.5%)31, Northeast, Ethiopia (33.2%)38, Southwest Ethiopia (41.5%)43, Dessie town hospitals, Ethiopia (37.9%)14, Ayder Referral Hospital, Ethiopia (42.6%)44, Sudan (45.9%)45, Tanzania (57.6%)46, Nigeria (69.3%)47, Saudi Arabia (55.1%)48, Qatar (48.4%)49, South India (52.1%)50, China (57.5%, 34.5%)32,51. Additionally, the prevalence of diabetic microvascular complications in this study is higher than the figure reported in a systematic review and meta-analysis conducted in low and middle-income countries (12%)52. These discrepancies could be attributed to variations in the diagnostic and screening methods or criteria for diabetic-related microvascular complications, as well as differences in access to healthcare services and the quality of diabetes management. Additionally, variations in the demographic and clinical characteristics of the study populations, differences in sample sizes, socio-demographic factors, and disparities in study periods might also explain the observed variations.

In the current study, T2DM patients aged 41–60 had lower odds of developing diabetic microvascular complications compared to those over 60 years old. This finding aligns with previous studies in Southern Ethiopia31, Saudi Arabia53, and China51, which showed that increasing age is associated with higher odds of developing diabetic microvascular complications. Additionally, studies from Dessie town hospitals14and Ayder Referral Hospital44in Ethiopia, as well as from India28, also indicated that older age is associated with the development of these complications. Aging is associated with structural and functional changes in the vascular system, including increased arterial stiffness and endothelial dysfunction, vascular calcification, reduced baroreceptor sensitivity, increased oxidative stress, and chronic inflammation, which collectively contribute to the heightened risk of microvascular complications in older adults with diabetes. These changes impair the ability of blood vessels to respond to metabolic demands and exacerbate the damage caused by hyperglycemia, making the management of diabetes in older populations particularly crucial29,54,55,56.

In agreement with previous studies done in Saudi Arabia27,17, Pakistan57, Turkey58, and Southern Ethiopia31. This study revealed that the odds of developing diabetic microvascular complications were two-fold greater among T2DM patients with poor glycemic control compared to those with good glycemic control. This can be justified by the fact that poor glycemic control leads to the formation of advanced glycation end products (AGEs), increased oxidative stress, chronic inflammation, endothelial dysfunction, activation of protein kinase C, and alterations in the polyol pathway. These biochemical changes collectively damage small blood vessels, causing microvascular complications. The thickening of basement membranes, increased vascular permeability, and endothelial cell dysfunction contribute to vision loss, kidney dysfunction, and nerve damage, highlighting the critical importance of maintaining optimal blood glucose levels to prevent these serious complications59,61,62,62.

Hypertension was another significant factor associated with the development of diabetic microvascular disorders. Compared to T2DM patients without a history of hypertension, those with a history of hypertension had greater odds of developing diabetic microvascular complications. This finding was supported by studies done in Ireland63, Spain64, Romania65,China32,51, Thailand30,Qatar49, Tanzania46,Dessie town hospitals, Ethiopia14and Southern Ethiopia31. Hypertension accelerates microvascular complications in diabetic patients by increasing intracellular hyperglycemia, which leads to oxidative stress, inflammation, and endothelial dysfunction. The heightened vascular pressure from hypertension further damages small blood vessels, leading to more rapid progression and increased severity of these complications66,67.

When interpreting the study’s findings, it is essential to consider certain limitations. Because of the study’s retrospective nature, we were unable to explore the effects of certain sociodemographic, clinical, and behavioral factors. Exploring these factors could have enriched the study by providing a more comprehensive understanding of how different aspects of a person’s background, medical history and current health status and behavior may influence the development of diabetic complications. Moreover, given the cross-sectional design of the study, establishing causal relationships between dependent and independent variables is difficult.

Conclusion

This study revealed that 1 in 5 patients with T2DM experienced at least one diabetic microvascular complication. Poor glycemic control and a history of hypertension were found to have a positive association with the development of these complications, while, being aged between 41 and 60 years showed a negative association. Early detection of these complications is crucial, highlighting the need for proactive interventions to manage modifiable risk factors such as poor glycemic control and hypertension that contribute to the onset of diabetic microvascular issues in individuals with T2DM.