Abstract
Introduction
This study aimed to identify the factors most strongly associated with an increased atherosclerotic cardiovascular disease (ASCVD) risk score in patients with type 2 diabetes (T2D).
Methods
This cross-sectional study included 4698 patients with T2D over an 11-year period (2010–2021). Patients were categorized into four groups based on their 10-year ASCVD risk score (< 5%, 5–7.5%, 7.5–20%, and > 20%). Multinominal regression analysis was used to evaluate the association between various modifiable and non-modifiable risk factors and the ASCVD risk score.
Results
Of the patients, 35.9% had a 10-year ASCVD risk score below 5%, 12.6% had a score between 5% and 7.5%, 30.8% had a score between 7.5% and 20%, and 19.7% had a score above 20%. Higher ASCVD risk scores were significantly associated with elevated waist-to-hip ratio (WHR > 0.93), pulse pressure, uric acid, triglycerides, and decreased glomerular filtration rate (all p-values < 0.05). WHR demonstrated the strongest association with higher ASCVD risk scores (OR: 4.55, 95% CI: 2.94–7.03, p < 0.001) when comparing patients with ASCVD scores > 5% to those with scores < 5%.
Conclusion
WHR was independently associated with higher ASCVD risk scores in patients with T2D. Incorporating WHR, along with traditional risk factors, could improve ASCVD risk assessments in this population.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12872-024-04297-w.
Keywords: Waist-to-Hip Ratio, Type 2 Diabetes, Cardiovascular Risk Score
Introduction
Atherosclerotic cardiovascular disease (ASCVD) includes conditions such as acute coronary syndrome, myocardial infarction, stable or unstable angina, cerebrovascular events (stroke, transient ischemic attack), and peripheral arterial disease, all caused by atherosclerosis [1]. Cardiovascular disease (CVD) continues to be a leading global health concern, with a 77% increase in risk between 1990 and 2019, affecting 523 million people by 2019 [2].
The ASCVD risk score, developed by the American College of Cardiology (ACC) and the American Heart Association (AHA), is a tool used to estimate the 10-year risk of a first cardiovascular event [3]. It is based on pooled cohort equations that consider various demographic and clinical factors, including age, gender, race, total and high-density lipoprotein (HDL) cholesterol levels, systolic blood pressure, use of antihypertensive therapy, presence of diabetes, and smoking status [3]. By categorizing patients into different risk groups, the ASCVD risk score offers guidance for clinical decision-making, particularly regarding initiating preventive measures like lipid-lowering therapy, lifestyle interventions, and blood pressure management [3].
Patients with Type 2 diabetes (T2D) face a significantly higher risk of cardiovascular complications [4]. In 2023, an estimated 536.6 million people globally were living with T2D, a number expected to reach 783.2 million by 2045 [5]. This burden is particularly high in Middle Eastern countries, including Iran, where both diabetes and CVD are increasing [6]. While traditional risk factors such as age, sex, cholesterol levels, hypertension, and smoking are well known, new evidence highlights additional contributors to ASCVD risk in patients with T2D [7, 8].
Several studies have demonstrated that beyond the conventional determinants of ASCVD risk, there are additional risk factors that significantly contribute to cardiovascular events and can be incorporated into new assessments [9]. Among anthropometric factors, waist-to-hip ratio (WHR) is a key indicator of central obesity, closely linked to visceral fat, which plays a critical role in cardiovascular risk [10]. WHR has demonstrated a stronger association with cardiovascular events than body mass index (BMI), making it a more reliable predictor of cardiovascular outcomes [10]. Elevated visceral adiposity, reflected in an increased WHR, contributes to chronic inflammation, endothelial dysfunction, and insulin resistance, all of which exacerbate CVD risk [11]. In addition, non-traditional factors like pregnancy, premature menopause, anxiety, and depression have been linked to increased cardiovascular events, despite not being part of conventional risk assessments [12, 13].
Although some evidence suggests a connection between anthropometric factors and the ASCVD risk score, the relative impact of various anthropometric factors on the ASCVD risk score in patients with T2D remains unclear [10, 14]. Therefore, this study aimed to identify which non-traditional and anthropometric factors are most strongly associated with an elevated ASCVD risk score in this population.
Methods
Study population
This cross-sectional study was conducted at a tertiary hospital affiliated with Tehran University of Medical Sciences (TUMS) over 11 years from 2010 to 2021. This investigation recruited patients with type 2 diabetes (T2D) who attended the hospital’s diabetes clinic during the study period. The diagnosis of diabetes was confirmed with the criteria set by the American Diabetes Association (ADA) [15]. Exclusion criteria comprise Patients with previous CVD history patients who had undergone PCI (percutaneous coronary intervention), CABG (coronary artery bypass graft) plus individuals who suffered from MI (myocardial infarction) or experienced acute coronary syndrome (ACS). Furthermore, patients with a glomerular filtration rate (GFR) of less than 30, those on dialysis, individuals diagnosed with cancer, or pregnant women were excluded. Prior to data collection, Written informed consent was obtained from all participating subjects. This survey was approved by the Tehran University of Medical Science Ethics Committee and conducted in confirming with 31 declarations of Helsinki 1975. (Ethical code: IR.TUMS.IKHC.REC.1400.086). All participants’ medical information was collected meticulously by qualified nurses (Supplementary Material 1).
Clinical assessment
Blood pressure was measured using calibrated Omron M7digital sphygmomanometers (Hoofddrop, The Netherlands) with 80% coverage of the upper arm. Participants were instructed to stay seated for 10 min, afterward first, second, and third blood pressure readings were recorded at the first, fifth, and tenth minutes, respectively. The mean value of the second and third blood pressure readings represented the systolic and diastolic blood pressure (SBP and DBP, respectively). Pulse pressure (PP) was quantified by subtracting systolic blood pressure from diastolic blood pressure. Height was measured utilizing an inflexible measuring tape with an accuracy of 0.1 cm patients were standing in a shoeless position from the soles of the feet to the top of the head. Weight was determined by a portable digital scale (Tefal PP1100) with an accuracy of 0.1 cm while patients wearing lightweight clothing. Body mass index (BMI) was calculated by employing weight (kg)/height(m²) formula. Waist circumference -mid (WC-mid) and hip circumference were measured using non-stretchable measuring tape while patients were in a vertical and calm posture The midpoint between costal margins and the iliac crest in a horizontal plane was designated as WC-mid. Hip circumference was obtained at the widest part of the hips in a horizontal plane. The waist-to-hip ratio (WHR) was computed by dividing waist circumference by hip circumference. The normal value of WHR is established as less than 0.9 in men and less than 0.8 in women. WHR > 0.93 was considered elevated WHR. (median). Estimated GFR(eGFR) was calculated using the Modification of Diet in Renal Disease (MDRD) equation in each participant [16]. In addition, patients were interviewed for family history of diabetes and CVD, duration of diabetes, and smoking status.
Laboratory evaluation
Following an overnight fast of 12 to 14 h, each patient’s blood was drawn and blood samples were collected for the biochemical experiments. The materials were centrifuged at 1500 revolutions per minute (RMP) for 10 min at a standard room temperature of 21 ֯ C and stored at a temperature of -70֯ C for quantifying laboratory measurements. Assessment of fasting blood sugar (FBS) and two-hour postprandial plasma glucose (2hpp) levels as well as lipid profiles comprising: total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) and creatinine (Cr) were conducted utilizing enzymatic, colorimetric method (GOD-POD) (Delta Darman Part Lab Test, Iran). HbA1c measurement was expressed by Direct Turbidimetry, Archem Diagnostics, Turkey. High-sensitivity C-reactive protein (hs-CRP) was determined using ELISA (Diagnostic Biochem, Canada, DBC kit, Canada). The intra- and inter-assay coefficient of variation ranged from 5.0 to 15.2%, with the lowest detectable concentration of hs-CRP being 0.01 mg/L. The normal value of hs-CRP is below 1 mg/dL [17].
ASCVD risk score assessment
The ASCVD risk score was calculated using the ACC ASCVD Risk Estimator Plus, which is available on the ACC website (tools.acc.org/ASCVD-RISK-ESTIMATOR-PLUS). This tool integrates several patient-specific variables, including age, sex, systolic blood pressure, smoking status, total cholesterol, HDL cholesterol, and the presence of diabetes, to estimate the likelihood of a major cardiovascular event over the next 10 years [18].
After estimating the ASCVD risk score for each patient, individuals were categorized into four risk groups based on their 10-year risk of developing ASCVD (Fig. 1) [3]:
Fig. 1.
Diagram of studied population
Low-risk group: ASCVD score of 0–4.9%.
Borderline risk group: ASCVD score of 5–7.4%.
Intermediate risk group: ASCVD score of 7.5–20%.
High-risk group: ASCVD score > 20%.
Statistical analysis
Data analysis was carried out by SPSS version 24.0 software. Continuous variables were represented as Mean and standard deviation (SD). The Kolmogorov-Smirnov test was used to test Normal distribution. To compare various features between 4 groups analysis of variance (ANOVA) and post-hoc analysis was conducted. Multinominal logistic regression analysis was employed to ascertain the association between various modifiable and non-modifiable risk factors and ASCVD risk categories. Additionally, linear regression was used to determine the relationship between WHR and the ASCVD risk score. Figure 2 was illustrated using Python version 3.12 with NumPy version 1.26 and Matplotlib version 3.8.1 libraries [19–21]. P value < 0.05 was deemed to be statistically significant.
Fig. 2.
Odds ratio of elevated waist-to-hip ratio in different ASCVD groups in comparison to group with ASCVD risk score < 5%
Results
This study included 4698 patients with T2D with an average age of 55.71 ± 11.03. Within the study population, 1,703 patients (35.9%) presented a 10-year ASCVD score below 5%, 598 (12.6%) exhibited an ASCVD score between 5 and 7.5%, 1,462 (30.8%) had a score ranging from 7.5 to 20%, and 935 (19.7%) demonstrated a score greater than 20%. A significant difference in mean age was observed among all groups (p < 0.001). Clinical characteristics, laboratory tests, demographic features, and anthropometric measurements corresponding to each ASCVD risk score category are shown in Table 1.
Table 1.
Comparison of clinical characteristics, laboratory findings, and disease history across ASCVD risk score categories
| variable | Total patients | ASCVD risk score | P-value | |||
|---|---|---|---|---|---|---|
| < 5 | 5-7.5 | 7.5–20 | > 20 | |||
|
Age (years) |
55.71 (11.03) |
46.01 (7.82) |
53.77 (5.94) |
59.35 (6.35) |
68.91 (6.76) |
< 0.001 |
| Duration of diabetes (years) |
8.61 (7) |
7.09 (5.94) |
7.89 (6.24) |
9.03 (7.11) |
11.13 (8.14) |
< 0.001 |
|
WC (centimeter) |
98.54 (10.72) |
97.89 (11.45) |
99.08 (10.79) |
99.28 (10.53) |
98.21 (9.44) |
0.001 |
| WHR |
0.93 (0.17) |
0.91 (0.06) |
0.93 (0.05) |
0.95 (0.3) |
0.95 (0.05) |
< 0.001 |
| CRP (mg/L) |
2.61 (32.21) |
3.75 (52.56) |
1.8 (2.39) |
1.99 (3.08) |
1.89 (2.91) |
0.744 |
| FBS (mg/dL) |
161.75 (54.81) |
164.57 (62.73) |
160.26 (58.86) |
160.1 (57.9) |
160.12 (54.81) |
0.108 |
| 2hpp (mg/dL) |
223.28 (91.55) |
221.79 (95.65) |
217.41 (85.61) |
223.68 (90.38) |
229.13 (89.29) |
0.083 |
| HbA1C (%) |
7.71 (1.67) |
7.7 (1.7) |
7.68 (1.64) |
7.73 (1.68) |
7.72 (1.65) |
0.934 |
| Uric acid (mg/dL) |
5.08 (2.28) |
4.89 (2.18) |
5.13 (2.79) |
5.13 (1.99) |
5.32 (2.49) |
< 0.001 |
| BMI (kg/m²) |
29.35 (5.17) |
30.08 (5.4) |
29.72 (5.29) |
29.36 (5.19) |
27.75 (4.21) |
< 0.001 |
| PP (mmHg) |
50.63 (28.66) |
43.95 (11.56) |
49 (12.41) |
52.29 (13.97) |
61.22 (57.31) |
< 0.001 |
| SBP (mmHg) |
129.9 (29.91) |
122.28 (13.86) |
128.38 (14.91) |
132.16 (16.43) |
141.21 (57.81) |
< 0.001 |
| DBP (mmHg) |
79.27 (8.7) |
78.33 (7.95) |
79.37 (8.13) |
79.86 (8.13) |
79.99 (9.69) |
< 0.001 |
| TG (mg/dL) |
176.48 (104.62) |
168.9 (96.86) |
189.02 (108.93) |
183.84 (110.89) |
170.82 (104.48) |
< 0.001 |
| TC (mg/dL) |
183.44 (44.9) |
180.39 (41.4) |
188.99 (43.76) |
185.61 (46.77) |
182.03 (44.9) |
< 0.001 |
| HDL (mg/dL) |
45.35 (11.81) |
47 (12.13) |
45.02 (12.26) |
44.68 (11.2) |
43.61 (11.51) |
< 0.001 |
| LDL (mg/dL) |
104.45 (40.32) |
102.57 (46.03) |
107.81 (36.52) |
105.29 (104.39) |
104.39 (37.04) |
0.037 |
| Cr (mg/dL) |
0.97 (0.23) |
0.9 (0.17) |
0.96 (0.2) |
0.99 (0.21) |
1.09 (0.29) |
< 0.001 |
| eGFR (mL/min/1.73 m²) |
70.82 (17.66) |
76.13 (17.21) |
70.15 (17.18) |
68.84 (16.12) |
64.68 (18.36) |
< 0.001 |
Data are presented as mean (SD)
WC: waist circumference; WHR: waist-to-hip ratio; CRP: C-reactive protein; FBS: fasting blood sugar; 2hpp: 2-h postprandial glucose; HbA1c: hemoglobin A1c; TG: triglycerides; BMI: body mass index; PP: pulse pressure; SBP: systolic blood pressure; DBP: diastolic blood pressure; Chol: cholesterol; HDL: high-density lipoprotein cholesterol; LDL: low-density lipoprotein cholesterol; Cr: creatinine; eGFR: estimated glomerular filtration rate
Waist circumference was higher in individuals with ASCVD scores between 7.5 and 20 compared to other score categories (97.89, 99.08, 99.28, 98.21 respectively; p = 0.001). Furthermore, patients with ASCVD scores between 5 and 7.5 exhibited the highest triglyceride and cholesterol levels (189.02; p < 0.001). The WHR values recorded for ASCVD risk score groups were 0.91, 0.93, 0.95, and 0.95, respectively (p < 0.001) (Table 1).
Individuals with ASCVD risk score < 5% demonstrated lower values of age, waist circumference, WHR, TG, uric acid, pulse pressure, SBP, DBP, Chol, Cr, and duration of diabetes (Table 1).
As shown in Table 2, multinominal regression analysis was conducted to evaluate the relationship between risk factors and elevated ASCVD risk score. The analysis revealed that increased uric acid levels, pulse pressure, triglyceride, and WHR are associated with higher odds of ASCVD scores. The increased duration of diabetes was correlated with higher odds of ASCVD scores above %20 compared to scores below %5 (OR = 1.048, 95% CI = 1.018–1.079, p = 0.002) (Table 2). Additionally, diminished estimated glomerular filtration rate (eGFR) levels were linked to higher odds of ASCVD risk scores across all groups compared to the reference group (scores below 5).
Table 2.
The results of multinominal regression analysis identifying independent risk factors associated with ASCVD risk scores
| variables | ASCVD risk score between 5 and 7.5 | ASCVD risk score between 7.5 and 20 | ASCVD risk score > 20 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| OR 1 | 95% CI | P-value | OR | 95%CI | P-value | OR | 95%CI | P-value | |
| Elevated WHR2 | 2.199 | 1.465–3.301 | < 0.001 | 3.039 | 2.16–4.276 | < 0.001 | 4.551 | 2.94–7.025 | < 0.001 |
| eGFR | 0.963 | 0.949–0.976 | < 0.001 | 0.954 | 0.938–0.969 | < 0.001 | 0.919 | 0.911–0.930 | < 0.001 |
| Duration of diabetes (years) | 0.977 | 0.945–1.01 | 0.164 | 1.018 | 0.993–1.044 | 0.156 | 1.048 | 1.018–1.079 | 0.002 |
| CRP | 0.966 | 0.947–1.047 | 0.872 | 0.999 | 0.988–1.01 | 0.859 | 1.002 | 0.99–1.014 | 0.765 |
| Uric acid | 1.257 | 1.106–1.429 | < 0.001 | 1.242 | 1.101–1.401 | < 0.001 | 1.249 | 1.083–1.441 | 0.002 |
| HBA1C | 0.973 | 0.854–1.11 | 0.687 | 0.931 | 0.833–1.04 | 0.205 | 0.942 | 0.819–1.083 | 0.4 |
| PP | 1.046 | 1.029–1.063 | < 0.001 | 1.07 | 1.055–1.084 | < 0.001 | 1.1 | 1.082–1.118 | < 0.001 |
| TG | 1.003 | 1.001–1.005 | 0.002 | 1.003 | 1.001–1.005 | 0.001 | 1.003 | 1-1.005 | 0.018 |
1: Group with ASCVD < 5% was used as reference
2: WHR > 0.93 (median)
OR: odds ratio; CI: confidence interval; ASCVD: atherosclerotic cardiovascular disease; eGFR: estimated glomerular filtration rate; CRP: C-reactive protein; HbA1c: hemoglobin A1c; PP: pulse pressure; TG: triglycerides; WHR: waist-to-hip ratio
After adjusting for the aforementioned factors, it was observed that WHR exhibited the strongest association with elevated ASCVD risk scores (OR = 4.55, 95% CI = 2.94–7.025, p < 0.001) (Fig. 2). Therefore, the results demonstrated that lower eGFR values, higher uric acid values, higher pulse pressure values, and higher triglyceride values were associated with increased ASCVD scores.
In the linear regression analysis, WHR was positively associated with the ASCVD risk score (B = 6.733, 95% CI: 3.928–9.537, p < 0.001).
Discussion
This study revealed that after adjusting for several confounding factors, including uric acid concentrations, pulse pressure, TG levels, and eGFR, increased WHR showed the most significant correlation with higher risk score for ASCVD.
Patients with T2D are at a much higher risk of developing cardiovascular events compared to those without T2D, leading to significantly elevated morbidity and mortality rates [22]. Therefore, a crucial strategy for managing patients with T2D involves systematically screening for cardiovascular risk factors and assessing the likelihood of future cardiovascular disease (CVD) events. Hence, estimating the 10-year ASCVD risk in individuals lacking a history of cardiovascular disease is facilitated through the use of the ACC/AHA risk calculator [18].
Numerous studies, including the one currently presented, have aimed to introduce risk enhancers in addition to traditional risk factors to help healthcare communities preventing cardiovascular diseases effectively [3]. According to a recent American Heart Association study, in addition to evaluating traditional risk factors, the assessment of factors including UACR (urinary albumin to creatinine ratio)andHbA1c may prove beneficial in predicting future cardiovascular events [23]. A novel finding of the present investigation is that among all risk factors assessed, WHR was identified as the most significant factor in increasing the ASCVD risk score. This finding underscores the importance of considering WHR measurements to prevent cardiovascular events in patients with diabetes. Consequently, it is strongly recommended to adopt proactive strategies within communities with T2D. This recommendation aligns with research by the Caribbean Health Outcomes Research Network (ECHORN), which studied the impact of various obesity related anthropometric measurements on ASCVD risk scores in the general population [24]. The study concluded that an increased WHR emerged as the most pivotal factor influencing ASCVD risk scores across all ASCVD risk categories within the general population [24]. Additionally, a study involving 143 participants demonstrated that WHR and waist circumference (WC) have a stronger correlation with lipid-related CHD risk factors compared to other anthropometric measures [25]. Czernichow et al. clarified that anthropometric parameters, specifically waist circumference and WHR, possessing an odds ratio of 1.1, were associated with the incidence of cardiovascular disease events in individuals diagnosed with type 2 diabetes. In the current investigation, we found that WHR had the highest odds ratio (4.55 [2.94–7.025]) among patients presenting with elevated ASCVD risk scores [26]. A systematic review by Coutinho et al. demonstrated that WC and WHR are superior to BMI in assessing mortality risk in patients with CAD [27]. It is recommended that WC, either alone or in conjunction with WHR, should be measured in normal-weight patients with CAD to enhance the classification of their condition and inform treatment strategies [27]. Furthermore, additional investigations have revealed that the association between WHR and visceral adiposity is significantly more pronounced compare to BMI [28–30]. As a result, this correlation has a more substantial impact on cardiovascular events among patients, both with and without diabetes [28–30]. In individuals with diabetes, BMI offers limited predictive value for future cardiovascular events. In contrast, more precise measures of visceral obesity, such as WHR, demonstrate a stronger correlation with metabolic disorders like blood lipid levels, and ultimately with cardiovascular events [26]. Visceral fat, commonly known as central fat, exhibits significant metabolic activity and is deposited around the body’s internal organs [31–33]. This particular type of fat, through various mechanisms, contributes to an increased risk of cardiovascular diseases [31–33]. Among these mechanisms, the release of free fatty acids (FFA) is particularly significant, as these fatty acids enter the circulatory system directly through the portal vein [31–33]. Elevated concentrations of FFAs, along with intra-abdominal fat accumulation, can precipitate insulin resistance, a critical factor in the development of type 2 diabetes and cardiovascular diseases [34]. On the other hand, visceral fat promotes production of inflammatory mediators such as cytokines and adipokines, resulting in chronic inflammation [34]. This inflammatory response is a crucial element linked to the progression of atherosclerosis, a central factor in the etiology of cardiovascular diseases [34]. Additionally, another deleterious consequence of intra-abdominal fat accumulation is dyslipidemia, characterized by high triglycerides and low HDL cholesterol levels, thus facilitating the development of atherosclerosis [35]. Furthermore, therapeutic interventions aimed at reducing adipose tissue and visceral fat in individuals with diabetes may help reduce the risk of future cardiovascular diseases. A research conducted by Tsioufis et al. on patients with hypertension (HTN) indicates that WC is a crucial independent variable in predicting future cardiovascular events [36]. Conversely, BMI and WHR did not independently serve as prognostic indicators for predicting cardiovascular events in their analysis [36]. Tsioufis et al. focused on a population of patients with HTN, while the current investigation exclusively included individuals with T2D of Iranian descent.
Additionally, this investigation revealed an inverse relationship between eGFR levels and the ASCVD risk score. This observation was further supported by a retrospective analysis conducted by Ren et al., which included a sample of 218 individuals diagnosed with diabetic kidney disease (DKD [37]. Furthermore, another study demonstrated that lower eGFR levels were associated with an increased 10-year ASCVD risk [38].
This research showed a positive association between triglyceride levels and ASCVD risk score among patients with diabetes. Elevated triglyceride levels have been shown to disrupt lipoprotein metabolism, leading to an increased risk of cardiovascular incidents [39–42]. Consequently, assessing triglyceride levels may serve as a diagnostic tool to identify patients with diabetes predisposed to cardiovascular diseases [40–42].
Elevated levels of uric acid have also been linked to an increased 10-year ASCVD risk score. This finding is consistent with a retrospective case-control study in Egypt, involving 108 patients with diabetes without a prior history of cardiovascular disease (CVD). The study revealed that high uric acid levels were significantly associated with elevated 10-year ASCVD risk scores [43]. Furthermore, research conducted by C.A. Jayashankar et al. supports the idea that uric acid is an independent prognostic indicator of coronary artery disease (CAD) among Asian Indian patients with diabetes [44]. However some studies offer conflicting evidence regarding this association, suggesting a potential lack of an independent relationship between uric acid levels and cardiovascular mortality in individuals with diabetes [45].
Another notable finding in this investigation was the association between pulse pressure and the ASCVD risk score. Several studies indicate a substantial correlation between pulse pressure and the likelihood of developing cardiovascular disease, with individuals with ASCVD having higher pulse pressure levels compared to those without the condition [46, 47]. Furthermore, pulse pressure has been identified as an independent variable in stroke and evaluating CVD risk in patients with T2D [48]. However a study by Theilade et al. suggests that pulse pressure does not serve as an independent prognostic factor for predicting future cardiovascular disease and an inverse relationship has been observed between pulse pressure and CVD risk among individuals with Type 2 diabetes [49]. The participants in the study by Theilade et al. had chronic kidney disease (CKD) and anemia alongside diabetes, which may affect the observed relationship between pulse pressure and cardiovascular disease risk.
A significant advantage of this research is its dual assessment of both laboratory and anthropometric factors, providing a comprehensive analysis. This is important as previous studies have not simultaneously examined the full spectrum of these factors. The participants in this study were exclusively of Iranian individuals diagnosed with T2D.
Given the cross-sectional design of this investigation, establishing a causal relationship between the variables studied is not feasible. However, the research effectively identified factors associated with increased risk of atherosclerotic heart disease. Longitudinal studies, such as cohort studies, could be specifically designed among Iranian patients to enhance understanding of the risk factors relevant to this condition. It is essential to note that certain potential confounding variables, such as physical activity and dietary habits, were not addressed in this investigation. Future research could be beneficial in yielding more generalizable findings regarding the factors contributing to an increased risk of heart diseases among patients with diabetes.
Conclusion
This investigation identified key determinants associated with an increased ASCVD risk score in individuals with T2D, including increased WHR, elevated uric acid, high TG levels, elevated pulse pressure, and decreased eGFR. Among the variables examined, WHR showed the strongest association with a higher ASCVD risk score, underscoring its importance in patients with T2D. As obesity rates rise globally, understanding WHR’s role in predicting cardiovascular events in diabetes is essential. Future research should focus on integrating WHR into clinical risk assessments.
Electronic Supplementary Material
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Acknowledgements
Not applicable.
Author contributions
Conceptualization: SR, MN, AE; Methodology: SK, KR, AY; Formal analysis: SR, SK, AY; Investigation: AET, ZA; Writing-original draft preparation: KR, AET, ZA; Writing-review and editing: SK, AY, SR, MN, AE; Supervision: MN, AE. All authors read and approved the final manuscript.
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Data availability
The data that support the findings of this study are available on request from the corresponding author.
Declarations
Ethics approval and consent to participate
This survey was approved by the Tehran University of Medical Science Ethics Committee and conducted in confirming with declarations of Helsinki. (Ethical code: IR.TUMS.IKHC.REC.1400.086). Informed consent was obtained from all individual participants included in the study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author.