Knowledge, risk perception, and associated factors of cardiovascular disease among adult with type 2 diabetic mellitus attending public hospitals in Addis Ababa, Ethiopia: A multicenter cross-sectional study

Abstract

Background

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in patients with type 2 diabetes mellitus. Understanding diabetes patients' knowledge and perception of CVD risk factors is essential for enhancing the quality of patient outcomes. This study aimed to assess the knowledge, risk perception, and factors associated with cardiovascular disease among adult patients with type 2 diabetes mellitus attending public hospitals in Addis Ababa, Ethiopia.

Methods

This cross-sectional study enrolled 389 participants via systematic random sampling from public hospitals in Addis Ababa, Ethiopia. Data were collected via a pre-tested structured questionnaire and analyzed using SPSS (version 27.0). Predictors of CVD knowledge and risk perception were identified through multivariable logistic regression. Statistical significance was defined as (P < 0.05) with 95% confidence intervals.

Results

Of 389 participants, 61.4% (95% CI: 56.6–66.2%) had good CVD knowledge and 43.4% (95% CI: 38.5–48.3%) demonstrated good risk perception. Factors significantly associated with good knowledge included secondary education (AOR = 6.15, P = 0.037), being married (AOR = 2.56, P = 0.018), and regular exercise (AOR = 2.63, P < 0.001), while history of smoking (AOR = 0.25, P < 0.001) and high-fat diet consumption (AOR = 0.23, P < 0.001) were inversely associated. Higher risk perception was independently predicted by age 41–64 years (AOR = 1.90, P = 0.032) and regular exercise (AOR = 2.35, P < 0.001).

Conclusion

This study highlights the need for targeted educational interventions to improve low CVD knowledge and risk perception among patients with type 2 diabetes mellitus, particularly addressing disparities by educational levels, marital status, age, and modifiable behavioral factors.

1. Introduction

Cardiovascular disease (CVD) is one of the leading causes of death worldwide and imposes a substantial health burden across populations. Studies on the global burden of disease reported that the number of CVD deaths increased from 13.1 million in 1990 to 19.2 million in 2023 [1]. Coherently, CVDs are the leading cause of death in low- and middle-income countries and are responsible for 80% of all deaths [2]. Moreover, CVD is a major public health challenge in Sub-Saharan Africa (SSA), accounting for 13% of annual deaths [3]. However, the impact of CVDs differs markedly between countries and regions because of several factors. Regions with a higher prevalence of risk factors and limited access to effective prevention and treatment have a greater burden of CVDs [4].

Existing evidence has shown that type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVDs) are interrelated chronic conditions that share common risk factors [5]. CVDs are a major cause of death and disability in people with type 2 diabetes mellitus [6]. In contrast, individuals with type 2 diabetes mellitus have a significantly increased risk of developing various cardiovascular complications, including heart attack, stroke, and peripheral vascular disease [7]. This indicates that poor glycemic control in diabetes leads to both microvascular and macrovascular complications, leading to heart disease, stroke, and peripheral vascular disease [8]. These co-occurring conditions due to diabetes mellitus and cardiovascular disease significantly increase morbidity and profoundly reduce a person's quality of life by increasing the overall disease burden, resulting in a high rate of mortality [6].

According to previous studies, many diseases such as high blood pressure, obesity, dyslipidemia, smoking, and poor blood sugar control are key risk factors for CVDs in people with T2DM [6], [9]. Other contributing factors include individual lifestyle, such as medication and dietary adherence, and the duration of treatment [10], [11]. The effects of sociodemographic status, including age, sex, educational level, duration of diagnosis [12], place of residence, and occupational status, have all been linked to CVD incidence and mortality among patients with type 2 diabetes mellitus [13]. Therefore, good knowledge and positive perceptions of CVD risk factors are crucial for preventing related complications.

Moreover, the perception of CVD risk in patients with diabetes mellitus plays a pivotal role in prevention and treatment adherence [14]. Nevertheless, subjective health perception promotes or hinders healthy behaviors in diabetic patients [15]. For instance, effective communication regarding healthy behaviors—such as maintaining a balanced diet, engaging in regular physical activity, and adhering to prescribed medications—can empower individuals with diabetes mellitus by enhancing their understanding of health risks, thereby promoting informed decision-making and positive behavioral changes that may, in turn, influence their perception of those risks [10], [16], [17]. This indicates that a strong perception of risk is generally linked to healthier lifestyle choices and preventive actions, as explained by the health belief model [18]. Hence, patients with chronic diseases are more likely to engage in preventive and better self-care actions if they perceive themselves at risk.

Furthermore, understanding how diabetes mellitus increases the risk of CVD is crucial for creating effective interventions, as patients' knowledge influences their self-management and adherence to treatments [19]. However, studies have demonstrated that many patients with diabetes mellitus have insufficient knowledge of the risk factors for CVDs [6], [11], [20]. Insufficient knowledge about CVD risk factors in people with diabetes leads to poorer health outcomes, indicating the need for targeted health educational programs to improve patient engagement and behavior change and ultimately reduce CVD complications and mortality [8], [21]. In fact, informed patients are more likely to adopt health-promoting behaviors, such as blood glucose control and lifestyle modification, reducing their risk of CVD and other diabetes mellitus-related complications [22].

The burden of CVD among people with T2DM in Ethiopia is high, with estimates from systematic reviews and meta-analyses ranging from 25% to 42% [6], [23]. Despite this burden, there is limited research in Ethiopia that assesses the knowledge and risk perception of CVD among patients with diabetes mellitus. Most studies conducted in Ethiopia have mainly focused on the knowledge of stroke and hypertension risk factors among patients with CVD [24], [25], [26]. To the best of our knowledge, no multicenter study has been conducted on the knowledge and risk perception of patients with diabetes mellitus regarding CVD risk factors in Addis Ababa. Therefore, this study aimed to assess knowledge, risk perception, and factors associated with CVD risk among adults with T2DM in Addis Ababa's public hospitals, Ethiopia. This study serves as a bridge by evaluating diabetic patients' perceptions and understanding of CVD and its risk factors. Moreover, identifying related risk factors allows healthcare providers to design targeted interventions and adapt preventive strategies and treatment plans to address the specific needs of patients with T2DM. This strategy can help improve the quality of care and promote better health outcomes in patients with chronic disease.

2. Methods and materials

2.1. Study design, area, and period

A cross-sectional study was conducted from January 1 to March 30, 2025, in the tertiary hospitals of Addis Ababa, the capital city of Ethiopia, and the headquarters of the African Union. Currently, the total population of the city is estimated to be approximately 5,956,680 [27]. The study setting comprised three randomly selected tertiary hospitals: Tikur Anbessa Specialized Hospital (TASH), ALERT Referral Hospital, and Kidus Petros Referral Hospital. These centers were selected due to their roles as primary referral sites for chronic non-communicable disease (NCD) management. Each facility maintains specialized follow-up clinics that provide standardized routine care and monitoring for patients with hypertension, heart disease, myocardial infarction, stroke and diabetes mellitus.

2.2. Population

All adults with a confirmed diagnosis of T2DM attending regular follow-up at selected public hospitals during the study period were considered as the source population. Additionally, diabetic patients aged ≥18 years, currently on follow-up, and who volunteered to participate were included in the study, while those who were seriously ill, had a mental problem, and were unable to respond or communicate were excluded from the study.

2.3. Sample size determinations

The sample size was calculated using a single population proportion formula: n $=\frac{{\left(\mathrm{Z}\right)}^2\left(\mathrm{P}\right)\left(1-\mathrm{P}\right)}{{\mathrm{d}}^2}$ . where $P=0.50$ (anticipated prevalence, selected due to lack of prior studies in the Ethiopian diabetic population), $Z_{\alpha /2}=1.96$ (critical value at 95% confidence level), and $d=0.05$ (margin of error). This yielded a minimum sample of 384. By adding 10% non-response rates, a final sample size of 422 was calculated for the study.

2.4. Sampling procedures

The calculated final sample size (n = 422) was allocated proportionally across sites based on preliminary estimates of monthly diabetic follow-up visits: Tikur Anbessa Specialized Hospital (n = 222), Kidus Petros Referral Hospital (n = 105), and ALERT Referral Hospital (n = 95). Daily clinic registration logs at each site formed the sampling frame of eligible patients, yielding a total anticipated sampling frame of N = 1267. Over the 3-month data collection period (TASH: N₁ = 667; Kidus Petros Referral Hospital: N₂ = 315; and ALERT Referral Hospital: N₃ = 285). Systematic random sampling was employed using site-specific intervals $K_i=N_i/n_i$. For all sites, this resulted in a sampling interval of K = 3: TASH ($667/222$), Kidus Petros Referral Hospital ($315/105$), and ALERT Referral hospital ($285/95$). Each day, a random start (1 to $K_i$) was selected via simple random draw from initial attendees; non-eligible patients and refusals were skipped to preserve the interval.

2.5. Data collection instruments

A structured and pre-tested questionnaire was adapted from previous studies [19], [28]. The instrument consists of four sections. The first section was used to collect the sociodemographic characteristics of the study participants, such as age, gender, marital status, education, income, residency, and BMI. This information was used to explore potential factors associated with diabetic patients' knowledge and perceptions regarding CVD risk factors.

However, the primary outcome of the study was the level of knowledge and risk perception of CVD among adults with T2DM. The second section consisted of 16 questions regarding knowledge of CVD risk factors. Each question had three response options: true, false, or do not know. This section aimed to evaluate the extent of diabetic patients' understanding of CVD and its associated risk factors. Scoring was based on assigning 1 point for each correct answer and 0 points for incorrect or “do not know” responses, resulting in a total knowledge score ranging from 0 to 16 points. We then summed up all the knowledge items for each participant. Higher scores indicate better knowledge of CVD risk factors. The third section consisted of eight questions assessing diabetic patients' perceptions related to CVD risk factors using a four-point Likert scale (strongly disagree, disagree, agree, strongly agree). Scoring was determined by assigning 2 points for “ strongly agree,” 1 point for “agree,” and 0 points for the rest (“strongly disagree and disagree”). The total practice score ranges from 0 to 16 points, with higher scores reflecting a greater perception of CVD risk factors.

The fourth section gathered information about patients' behavioral factors affecting cardiovascular disease knowledge and perception. This section had two response options: “Yes and No.” The respondent's correct and incorrect responses provided for the questions were given “1” and “0” points, respectively.

The questionnaire was initially developed in English and translated into Amharic (the federal language) by bilingual experts fluent in medical terminology, and backward-translated into English by independent translators blinded to the original version. Then, the questionnaires were tested for internal consistency reliability, yielding a Cronbach's alpha coefficient of 0.82. The Amharic questionnaire underwent pilot testing on 5% of patients attending Yekatit 12 Hospital & Medical College to refine wording and administration. Data were collected via structured face-to-face interviews by three trained BSc nurses, with participants purposively recruited from cardiology follow-up clinics using consecutive appointment sampling. The principal investigator conducted daily reviews to ensure data completeness (>98%) and fidelity to the protocol.

2.6. Statistical analysis

The collected data were checked, cleaned, entered into EpiData software 3.1, and exported to SPSS version 27.0 software for analysis. Incomplete and inconsistent data were excluded from analysis. Descriptive statistics, such as frequency, percentage, mean, and standard deviation, were used to describe each variable, while inferential statistics (binary and multiple logistic regression analysis) were used to test the association of the independent variables with the dependent variable. The assumption of data normality was checked using the Kolmogorov-Smirnov and Shapiro-Wilk tests, along with histograms, and was found to be satisfactory. An Odds ratios (OR) with 95% confidence intervals (CI) were used to measure the strength of this association. Statistical significance was set at P-value <0.05. The data are presented in tables, figures, and graphs.

2.7. Operational definition

Good knowledge of cardiovascular disease (CVD): Defined as the information and understanding of patients have about CVD, including its risk factors, symptoms, and preventive measures. This can be quantified as an individual who answered 73% or more of the questions provided [29].

Good perception of cardiovascular disease (CVD): Refers to the beliefs, attitudes, and subjective interpretations of diabetic patients regarding their risk of developing CVD. It was measured by answering 75% of the provided questions. [30]. Behavioral factors mean the factors that directly or indirectly increase the likelihood of cardiovascular disease. These include tobacco use, alcohol consumption, exercise, and high-fat dietary intake [7].

3. Results

3.1. Sociodemographic characteristics of the participants

A total of 389 patients diagnosed with T2DM, who followed up at selected hospitals, were

enrolled in the study, yielding a 92.2% response rate. The mean age was 52 years (±16.6), with 53% female and 59.1% residing in urban areas. Most participants were married (67.9%), had completed secondary school (27.2%), or held a college/university degree (26.7%). About 30.1% earned less than 4000 ETB monthly, and 40.6% had lived with diabetes mellitus for over 10 years. More than half (53.7%) had a normal BMI, whereas 29.3% were overweight (Table 1)

Table 1.

Sociodemographic characteristics of the study participants at public hospitals of Addis Ababa, Ethiopia (n = 389).

Variables	Characteristics	Frequency (n)	Percent (%)
Age Group	18–40 years	102	26.2
	41–64 years	178	45.8
	≥65 years	109	28.0
Gender	Female	206	53.0
	Male	183	47.0
Educational background	No formal education	59	15.2
	Primary level	84	21.6
	Secondary level	106	27.2
	College/University	104	26.7
	Postgraduate degree	36	9.3
Marital status	Widowed	71	18.3
	Married	264	67.9
	Divorced	48	12.3
	Not married	6	1.5
Income	< 4000 ETB	117	30.1
	4000–6500 ETB	91	23.4
	6501–10,000 ETB	80	20.5
	> 10,000 ETB	101	26.0
Residency	Rural	159	40.9
	Urban	230	59.1
Duration of DM	< 5 years	106	27.3
	5–10 years	125	32.1
	> 10 years	158	40.6
BMI	<18.5	13	3.4
	18.5–24.9	209	53.7
	25–30	114	29.3
	>30	53	13.6

Note: BMI: body mass index, ETB: Ethiopian birr.

3.2. Behavioral characteristics of the participant

As presented in Table 2, this study evaluated the lifestyle behaviors of study participants related to cardiovascular risk, including regular exercise, tobacco use, diet, and daily alcohol consumption. About 58.6% of participants engaged in regular moderate physical activity, and only 21% reported current tobacco use. Fat-rich foods were consumed daily by 34.7% of respondents, while 65.3% avoided them. Daily alcohol consumption was reported by 24.9%, whereas 75.1% did not consume alcohol regularly. Overall, the findings suggest a relatively low prevalence of tobacco and alcohol use among the participants.

Table 2.

Behavioral characteristics of study participants at the selected public hospitals of Addis Ababa, Ethiopia (n = 389).

Characteristics	Response	Percentage (%)
Engage in regular physical exercise	No	41.4%
	Yes	58.6%
Tobacco use	No	79%
	Yes	21%
Consuming fatty foods in daily diet	No	65.3%
	Yes	34.7%
Daily alcohol consumption	No	75.1%
	Yes	24.9%

3.3. Knowledge and risk perception of cardiovascular disease among study participants

Among 389 participants interviewed, 61.4% (95% CI: 56.6–66.2%) demonstrated good knowledge of CVD risk factors, while 43.4% (95% CI: 38.5–48.3%) had a good level of perception. This suggests that, although most participants possessed relatively good knowledge, over half underestimated their own risk, emphasizing the absence of a relationship between knowledge levels and risk perception. Fig. 1 shows the percentages of knowledge and risk perception of cardiovascular disease among the study participants.

Fig. 1.

Knowledge and risk perception level of type 2 diabetic patients on CVD risk factor (n = 389).

3.4. Factors associated with participants' knowledge level

As presented in Table 3, both bivariate and multivariate analyses were performed to identify the factors associated with knowledge of CVD risk factors. In bivariate regression analysis, age, marital status, education, residence, and income were significantly associated with participants' knowledge of CVD risk factors. After controlling for the effects of potentially confounding variables, only five variables were significantly associated with knowledge of the CVD risk factors. Accordingly, attending secondary education (AOR = 6.148, 95% CI: 1.120–3.743, P = 0.037), being married (AOR = 2.557, 95% CI: 1.175–5.564, P = 0.018), and engaging in regular physical exercise (AOR = 2.629, 95% CI: 1.558–4.436, P < 0.001) were significantly associated with a good level of knowledge regarding CVD risk factor. However, those who were smokers had 75% lower odds of good knowledge compared to non-smokers (AOR = 0.250, 95% CI: 0.132–0.471, P < 0.001), and those who consumed high fatty foods had 77.2% lower odds of good knowledge compared to non-consumers of high fatty rich foods (AOR = 0.228, 95% CI: 0.133–0.389, P < 0.001). Alcohol consumption, however, was not significantly associated with respondents' knowledge of CVD risk factors (AOR = 0.728, 95% CI: 0.400–1.325, P = 0.299).

Table 3.

Bivariate and multivariate regression analysis of factors associated with knowledge of study participants toward CVD risk factors (n = 389).

Variables	Knowledge		COR (C·I 95%)	AOR (C·I 95%)	Sig.
	Good	Poor			P-value
Residency
Urban	80	79	1	1	1
Rural	159	71	0.452 (0.298–0.687) ⁎⁎	0.869 (0.510–1.482)	0.869
Income
<4000	62	55	1	1	1
4000–6500	56	35	1.571 (0.842–0.929)	1.312 (0.617–2.793)	1.312
6500–10,000	49	31	1.012 (0.5461–0.876)	1.408 (0.639–3.104)	1.408
>10,000	72	29	0.713 (0.400–0.721)	1.304 (0.619–2.746)	1.304
Educational background
No formal educ.	23	36	1	1	1
Primary school	45	39	2.390 (1.330–4.296) ⁎	0.441(0.169–1.153)	0.095
Secondary school	59	47	0.509 (0.266–0.973) ⁎	6.148 (1.120–3.743)	0.037⁎
College/university	78	26	1.542 (3.093–5.293) ⁎	0.558 (0.254–1.227)	0.147
Post graduate	34	2	0.919 (0.517–1.634)	0.632 (0.318–1.256)	0.190
Marital status
Widowed	27	44	1	1	1
Divorced	34	14	3.958 (1.804–8.681) ⁎	2.555(0.910–7.173)	0.075
Married	177	87	3.315 (1.925–5.710) ⁎	2.557 (1.175–5.564)	0.018⁎
Not married	1	5	0.326 (0.036–2.941)	0.356 (024–5.178)	0.449
Age in the group
18–40	65	37	1	1	1
41–64	116	62	1.545 (1.504–8.643)	0.804 (0.371–1.741)	0.580
≥ 65	58	51	1.645 (1.011–2.676)	0.847 (0.438–1.637)	0.621
Regular exercise
No	120	41	1	1	1
Yes	119	109	0.373 (0.240–0.579) ⁎	2.629 (1.558–4.436)	0.000⁎⁎
Tobacco use
No	207	100	1	1	1
Yes	32	50	3.234 (1.954–5.353) ⁎	0.250 (132–0.471)	0.000⁎⁎
Consuming high-fat food
No	52	83	1	1	1
Yes	187	67	4.455 (2.855–6.952) ⁎	0.228 (0.133–0.389)	0.000⁎⁎
Daily consuming alcohol
No	53	44	1	1	1
Yes	186	106	1.457 (0.915–2.320)	0.728 (0.400–1.325)	0.299

Note: AOR = adjusted odds ratio; COR = crude odds ratio; CI = confidence interval; 1 = reference

^⁎statistically significant at p < 0.05.

^⁎⁎statistically significant at p < 0.001.

3.5. Factors associated with the risk perception of CVD among study participants

As illustrated in Table 4, multivariable logistic regression analysis identified several factors associated with the risk perception of cardiovascular disease (CVD) among adult patients with type 2 diabetes mellitus. Marital status was strongly associated with risk perception. Participants aged 41–64 had nearly twice the odds of high perception compared to those aged 18–40 (AOR = 1.898, 95% CI: 1.057–3.410, p = 0.032), Further, this study showed that individuals who engaged in regular exercise (AOR = 2.354, 95% CI: 1.486–3.732, P < 0.001) had higher perception of CVD risk factors compared to those who did not engage in regular exercise. However, patients who consumed fatty foods (AOR = 1.202, P = 0.448) or alcohol (AOR = 0.795, P = 0.397) did not demonstrate significant differences in perception compared with those who did not consume fatty foods or alcohol.

Table 4.

Bivariate and multivariate regression analysis of factors associated with the perception of study participants toward CVD risk factors (n = 389).

Variables	Perception		COR (C·I 95%)	AOR (C·I 95%)	Sig.
	High	Low			P-value
Duration of DM
<5 years	44	62	1	1	1
6–10 years	85	73	1.508(0.880–2.585)	0.916 (0.514–1.631)	0.765
>10 years	40	85	2.474 (1.517–4.035) ⁎	0.632 (0.352–1.135)	0.125
BMI
<18.5	3	10	1	1	1
18.5–24.9	86	123	0.213 (0.052–0.864) ⁎	2.154 (0.511–9.084)	0.296
25–29.9	49	65	0.496 (0.269–0.915) ⁎	2.352 (0.542–10.202)	0.253
>30	31	22	0.535 (0.276–1.035)	3.504 (0.766–16.33)	0.106
Marital status
Widowed	53	18	1	1	1
Divorced	15	33	0.145 (0.069–0.348)	0.166 (0.064–0.432)	0.092
Married	100	164	0.207 (0.115–0.373)	0.215 (0.106–0.434)	0.060
Not married	1	5	0.068 (0.007–0.621) *	0.103 (0.010–1.036)	0.055
Age groups
18–40	29	73	1	1	1
41–64	79	99	0.371 (0.176–0.558) *	1.898 (1.057–3.410)	0.032⁎
≥65	61	48	0.628 (0.158–0.389)	1.590 (0.778–3.732)	0.203
Regular exercise
No	85	76	1	1	1
Yes	84	144	0.522 (0.346–0.768) ⁎	2.354 (1.486–3.732)	0.000⁎⁎
Consuming high-fat food
No	66	69	1	1	1
Yes	103	151	0.713 (0.486–1.086)	1.202 (0.748–1.931)	0.448
Daily alcohol consumption
No	35	62	1	1	1
Yes	134	158	1.502 (0.935–2.413)	0.795 (0.469–1.350)	0.397

Note: AOR = adjusted odds ratio; COR = crude odds ratio; CI = confidence interval; 1 = reference

^⁎statistically significant at p < 0.05.

^⁎⁎statistically significant at p < 0.001.

4. Discussion

Globally, cardiovascular disease (CVDs) is a major cause of death and disability among people with type 2 diabetes mellitus [6], and the burden of CVD among people with T2DM is very high in low-income countries, including Ethiopia [6], [23]. Evaluating knowledge and risk perception of CVD among patients with diabetes mellitus is vital for improving patient outcomes. This study aimed to assess the knowledge, risk perception, and associated factors of cardiovascular disease among adults with T2DM attending public hospitals in Addis Ababa, Ethiopia. Overall, this study found that the level of knowledge and perception of CVD risk factors among patients with diabetes was low. Patients' low levels of knowledge and poor perception of CVD risk factors can negatively affect the quality of patient outcomes. Additionally, our findings indicate that sociodemographic characteristics—specifically age, education level, and marital status—alongside behavioral factors, such as regular physical activity, tobacco use, and high-fat dietary intake, were significantly associated with adequate CVD knowledge.

The current study showed that 61.4% of participants had good knowledge of CVDs. This finding is consistent with a previous study conducted in developing countries such as Ethiopia [28], Uganda [11], Nigeria [17] and Turkey [20] suggesting that significant efforts are still needed to enhance awareness and understanding of CVD and its associated risk factors in low- and middle-income countries. Most importantly, targeted interventions are needed to reduce the development of macrovascular and microvascular complications in T2DM. To achieve this, it is essential to identify high-risk groups, such as patients, families, and communities, and implement preventive programs, including continuous educational initiatives tailored to these populations.

In the present study, only 43.4% of participants exhibited a high level of risk perception. This finding is consistent with a study reported in Tanzania [31], which showed that the majority of participants had a low level of awareness of CVD risk factors. An inadequate perception of CVD risk among diabetic patients results in underestimating their actual risk, reduced adherence to preventive measures, and ultimately, poorer health outcomes [32]. In contrast, this finding is lower than that reported in a study of Saudi Arabia [22]. This variation could be due to differences in sociodemographic characteristics, study setting, sample size, and patient experience of using different sources of information regarding the prevention and early treatment of diabetes mellitus and its related factors. For instance, existing research suggests that the risk perception of a patient is not only influenced by knowledge of the patient but also by internal factors, such as illness beliefs and the sociocultural context of diabetes mellitus self-management [33].

Another interesting finding of this study was the significant relationship between patients' educational level and good knowledge regarding CVD risk factors. Participants with a secondary educational level were more likely to be knowledgeable about CVD. This finding is supported by previous studies conducted in Uganda [11], Saudi Arabia [22] and Turkey [20] suggesting that those with lower levels of education require particular attention. In fact, education improves the ability to understand health information, encourages more proactive health-seeking behaviors by reading educational materials, and enables individuals to participate more effectively in health consultations.

This study found that married individuals demonstrated higher odds of adequate CVD knowledge compared to widowed individuals. This finding is consistent with previous studies in Ethiopia [28], which suggests that marital status may provide social support mechanisms that facilitate cardiovascular health awareness. Additionally, a recent meta-analysis conducted on the association between marital status and cardiovascular diseases [34] suggested an increased risk of CVD incidence among divorced and widowed people compared with married people. A possible reason could be spousal support, which often facilitates health-seeking behavior and may provide opportunities for shared learning and the mutual reinforcement of healthy behaviors.

Furthermore, our results indicate that a history of tobacco use was inversely associated with CVD knowledge, with smokers demonstrating significantly lower odds of adequate awareness compared to non-smokers. This aligns with findings from Cameroon [35], which suggested that non-smokers generally possess a more comprehensive understanding of cardiovascular risk factors and preventive strategies. This discrepancy may be attributed to enhanced health-seeking behaviors among non-smokers, who often demonstrate greater receptivity to health communication. Such engagement likely facilitates a more robust understanding of pivotal CVD prevention factors, including dietary management and physical activity.

The current study revealed that being aged between 41 and 64 years had nearly twice the odds of having a high perception of CVD compared to those aged 18–40 years. This finding is supported by a study conducted in Morocco [36], in which middle-aged adults had a higher perception of CVD risk factors than younger adults. This may be due to a combination of biological, experiential, and informational factors. As people age, they are often more aware of health risks, particularly those related to CVD, owing to increased exposure to health information, screenings, and medical advice. Evidence suggests that CVD and its risk factors, such as hypertension, high cholesterol, and diabetes mellitus, become more prevalent with age [37], which may heighten individuals' perceptions of their vulnerability. Our study showed that participants who engaged in physical exercise demonstrated a higher perception of CVD risk prevention than did those who did not.

Evidence suggests that embracing healthy lifestyle habits enhances overall health-related quality of life [2]. This study demonstrated that engaging in regular physical exercise is significantly associated with a higher perception of CVD risk prevention. Similarly, a study conducted in Saudi Arabia found a significant association between physical activity and increased risk perception regarding CVD prevention among patients [32]. This disparity indicates that simply engaging in physical activity is more beneficial for improving the blood circulation and normal functioning of the heart than for those who do not consistently engage in physical exercise. Encouragingly, over half of the respondents engaged in physical activity and avoided fatty foods, and a significant majority (78.9%) reported never smoking. These practices reflect a positive trend toward health-promoting behaviors. Compared to a previous study in Southwest Ethiopia, fewer patients recognized smoking and diet as risk factors [28]. These findings suggest that behavior-based education, particularly the integration of non-communicable disease education into diabetes mellitus clinics, has a positive impact.

While alcohol consumption is a well-established risk factor for cardiovascular disease [10], [19], [22], our findings revealed no significant difference in CVD risk perception between alcohol consumers and their counterparts. This lack of divergence may stem from variations in study populations, sample sizes, or sociocultural norms and personal beliefs that shape health risk assessments. Furthermore, the nuances of consumption such as duration and quantity warrant consideration; participants may not perceive infrequent or low-volume alcohol intake as a substantial threat to cardiovascular health. This ‘optimistic bias regarding moderate habits, similar to the occasional consumption of high-fat foods, may attenuate the perceived urgency of behavioral modification.

4.1. Strengths and limitations of the study

The strengths of this study include its high response rate and data collection through patient interviews. The study was performed in the only diabetic care center in Ethiopia, where patients come to this center from all over Ethiopia; hence, the results of this study can represent the whole population. The study also revealed significant findings regarding the patients' knowledge and risk perception of CVD. However, this study has some limitations. One limitation is recall bias because of the self-reported evaluation of knowledge and risk perception. Nevertheless, this suggests that the actual situation could be worse in developing countries, including Ethiopia, highlighting the urgent need for action. In addition, a cross-sectional study design limits causal inference as it cannot determine the direction between knowledge, perception, and behavior. Additionally, we did not measure objective clinical parameters, such as lipid profiles, blood pressure, or HbA1c, that could affect an individual's risk perception and intention toward a healthy lifestyle. The study also primarily focused on cognitive and behavioral aspects, lacking exploration of the emotional, psychological, and cultural factors that significantly influence risk perception and health behaviors. Therefore, future studies are recommended to investigate the longitudinal causes of low awareness and risk perception and assess the impact of culturally tailored interventions.

4.2. Implications of the study

The findings of the current study have practical implications for healthcare providers and policymakers to recognize the need for change, aiming to enhance diabetic patients' awareness of CVD risk factors and mitigate the prevalence of CVD risk behaviors among patients with chronic diseases such as diabetes mellitus, hypertension, and heart failure. Furthermore, healthcare providers should identify patients who have limited awareness of risk factors, engage in actual risk behaviors, and offer customized interventions accordingly.

5. Conclusion

This study suggests that the overall knowledge and risk perception of cardiovascular disease among patients with T2DM in the study area were low. Patients' educational level, marital status, and engagement in physical activities were significantly associated with good knowledge of CVD risk factors. Similarly, age and physical exercise were significantly associated with a higher perception of CVD risk factors. However, being a smoker and a consumer of high-fat foods was associated with lower knowledge of CVD risk factors. Therefore, healthcare providers should design targeted educational programs that address misconceptions and improve personal risk perception of CVD. Policymakers should strengthen community-based health promotion and integrate behavior-focused strategies into diabetes care.

CRediT authorship contribution statement

Abnet Tsegaye Tolla: Writing – review & editing, Writing – original draft, Validation, Methodology, Investigation, Data curation, Conceptualization. Daniel Mengistu: Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Project administration, Methodology, Funding acquisition. Debela Gela: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Methodology, Conceptualization. Boka Dugassa Tolera: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.

Ethical approval

The Institutional Review Board of Addis Ababa University College of Health Science approved this study (Ref number: AAU-IRB/NUR/2025). This study was conducted in accordance with the Declaration of Helsinki. An official letter was written to the selected governmental hospitals and permission was obtained from the respective hospitals. Participation in the study was entirely voluntary, and participants were free to leave at any moment, as noted on the participant information sheet. Prior to the data collection, each participant signed an informed consent form. All personal identifiers were omitted throughout data collection, and the collected data were stored in locked storage. Only the principal investigator had access to the data.

Declaration of Generative AI and AI-assisted technologies in the writing process

During the preparation of this study, the authors did not use any generative AI or AI-assisted technologies in the writing process.

Funding

The authors received no financial support for the research, authorship, or publication of this manuscript.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.