Uncontrolled hypertension in patients with type 2 diabetes: What are the correlates?

Abstract Suboptimal blood pressure (BP) control in patients with type 2 diabetes is associated with adverse micro‐ and macrovascular complications. This study aimed to investigate the predictors of uncontrolled hypertension in an Iranian population with type 2 diabetes. This is a cross‐sectional study of 2612 patients with type 2 diabetes, including 944 patients with hypertension. Controlled and uncontrolled hypertension were assessed. Multivariate logistic regression modeling was used to determined independent predictors of uncontrolled hypertension. Of 2612 patients with type 2 diabetes, 944 (36.1%) patients had hypertension. Of all patients with hypertension, 580 (61.4%) were still on monotherapy. Uncontrolled hypertension was detected in 536 participants (56.8%). Patients with uncontrolled hypertension had significantly higher body mass index (BMI) (29.8±4.8 vs. 28.6±4.6), waist circumference (99.11±10.95 vs. 96.68±10.92), pulse pressure (67.3±17.3 vs. 48.4±10.7), total cholesterol (177.1±45.5 vs. 164.3±40.5), non‐HDL cholesterol (133.0±43.5 vs. 120.1±38.7), triglycerides (175.7±80.3 vs. 157.4±76.7), and Atherogenic Index of Plasma (AIP) (0.57±0.23 vs. 0.52±0.24) (p < .05 for all of them) compared to patients with controlled hypertension. Multivariate logistic regression analysis revealed that uncontrolled hypertension was significantly associated with BMI (p = .001), pulse pressure (p = .001), total cholesterol (p = .006), and non‐HDL cholesterol (p = .009). In patients with triglycerides levels > 200 mg/dl non‐HDL cholesterol had a significant correlation with uncontrolled hypertension (OR = 4.635, CI95%:1.781–12.064, p = .002). In conclusion, BMI, pulse pressure, total cholesterol, and non‐HDL cholesterol are significant predictors of uncontrolled hypertension in patients with type 2 diabetes. Also, ineffective monotherapy, medical inertia and patients’ non‐compliance were other contributors to the uncontrolled hypertension.


INTRODUCTION
International Diabetes Federation (IDF) statistics of 2019 showed that the global prevalence of diabetes between the ages of 20 and 79 years is 9.3%. There were 54.8 million people with diabetes in the middle east and north Africa region in 2019, and this number is expected to rise to 107.6 million in 2045. 1 The prevalence of hypertension among patients with type 2 diabetes is relatively high. This elevated blood pressure (BP) exacerbates both micro-and macrovascular complications of diabetes mellitus, including retinopathy, nephropathy, coronary artery disease, an impact illustrated particularly in the ADVANCED trial. [2][3][4][5][6] It is well documented that reducing BP when systolic BP values are higher than140 mm Hg is associated with a reduction in cardiovascular mortality among diabetic patients with hypertension. 7 As demonstrated by the hypertension optimal treatment study (HOT) trial and systolic hypertension in Europe (Syst-Eur) study, patients with diabetes and hypertension experience lower rates of adverse cardiovascular events after BP control compared with patients without diabetes. 8,9 According to the United Kingdom prospective observational study, in patients with diabetes, every 10 mm Hg reduction in mean systolic BP decreased diabetic-related deaths by 15%, myocardial infarction by 11%, and microvascular complications by 13%. 10 However, even with the apparent benefits regarding BP control, a recent report of the national program for prevention and control of diabetes in Iran showed that 56.7% of patients with concurrent hypertension and diabetes had uncontrolled BP. 11 Various studies had conducted to determine the main predictors of uncontrolled hypertension to help better strategize national health policies. [12][13][14] However, determinants of uncontrolled hypertension among patients with diabetes need to be further studied. Given the importance of this matter, we aimed to investigate predictors of uncontrolled hypertension among patients with diabetes attending the diabetes clinic of Vali-Asr Hospital.

Study design and patients
This was a cross-sectional study using the data extracted from an ongo- The unadjusted cross-tabulation analysis showed significant differences only in the distribution of categorized BMI, total cholesterol, triglyceride, non-HDL-C, and AIP. AIP was categorized by its median (Table 2).
Logistic regression models after adjusting for other variables were shown in Table 3. Models revealed that higher BMI, higher pulse pressure, higher cholesterol and, higher non-HDL-C were more preva- In Table 4, patients were stratified based on serum triglyceride levels lower and higher than 200 mg/dl. Binary logistic regression showed that higher levels of non-HDL-C had a stronger correlation with uncontrolled hypertension among patients with serum triglyceride levels of more than 200 mg/dl (OR = 4.635, CI95%:1.781-12.064, p = .002) ( Figure 1). Also, in patients with serum triglyceride levels higher than 200 mg/dl, the correlation between BMI and uncontrolled hypertension did not remain significant (p = .798).

DISCUSSION
This study highlighted four important characteristics associated with uncontrolled hypertension among patients with diabetes, including BMI, pulse pressure, total cholesterol, and non-HDL cholesterol.

BMI
This study pointed out that BMI is a significant predictor for uncon-  19 increased free fatty acids, 20 renin-angiotensin system activation, 21 and angiotensin II production in adipose tissue. 22 Hyperinsulinemia, a connecting factor between obesity, diabetes, and metabolic syndrome, is also associated with hypertension through anti natriuretic, sympathomimetic effects, and RAS activation. 23 Furthermore, obesity has been considered a major risk factor for Obstructive sleep apnea (OSA). A strong body of evidence has shown the bidirectional association between OSA .001 Multivariate logistic regression analysis was used to calculate significant predictors of uncontrolled hypertension after adjusting for other variables. Abbreviations: BMI, Body mass index; Ref, Reference group; AIP, Atherogenic index of plasma; non-HDL-C, Non high density lipoprotein cholesterol; 95%CI, 95% confidence interval; OR, Odds ratio. and hypertension. 24 Although the number of patients with OSA is not provided in this study, given the strong relationship between obesity and OSA and the higher rate of obesity in this cohort, it can be estimated that the higher rate of uncontrolled hypertension is partly attributed to the OSA in the patients with higher BMI values.

Metabolic syndrome
Metabolic syndrome is a major cause of cardiovascular mortality. 25 In this study prevalence of metabolic syndrome for patients with controlled and uncontrolled hypertension was 87.2% and 90.8%, respectively. These numbers are higher than the national prevalence of metabolic syndrome, which is 32.9% for the Iranian population. 26 Walter Zidek and colleagues showed that in patients with hypertension, BP control which was not achieved by antihypertensive therapy, was associated with metabolic syndrome and its components.
Nevertheless, we didn't see any association between uncontrolled hypertension and metabolic syndrome. This might partly be because all of our patients already had two of the metabolic components including diabetes, and hypertension. However, the former study population was not limited to diabetic patients. 27

Pulse pressure
Pulse pressure which is the difference between systolic and diastolic BP is known to be a significant independent risk factor for cardiovascular mortality. 28 Blacher J and colleagues calculated an increased risk of coronary disease by 13% and cardiovascular mortality by 20% with every 10 mm Hg increase in pulse pressure. 29 We observed a positive association of uncontrolled hypertension with wide pulse pressure.
Higher pulse pressure associated with uncontrolled hypertension in diabetes amplifies cardiovascular events in this subset of patients. Tar

Lipids
We observed that higher triglycerides, total cholesterol, and non-  42 There are several reasons behind this recommendation, particularly medical inertia defined as failure of health care providers to intensify treatment when indicated 43 and patients' non-compliance to the therapy, a factor with much more importance than previously anticipated. 44 In this cohort, not only patients with hypertension received insufficient treatment despite inadequate control of BP levels, but also patients on oral anti diabetic monotherapy had markedly elevated levels of HbA1c, reflecting high rates of medical inertia or individuals' non-compliance. This is in line with previous data showing endorsement of ineffective monotherapy or suboptimal doses in spite of undesirable results in many patients 45 in addition to low adherence to the treatment. 44 Interestingly, it has been demonstrated that 60% of all patients candidate for dual therapy, are still under monotherapy. 45 This is in line with the 61.4% monotherapy rate among all patients with hypertension, reported in this study.

Limitations
The cross-sectional nature of our study makes it hard to conclude the causality between the predictors and the outcome variable. Also, the number of patients with OSA was not available.

CONCLUSIONS
Although most hypertensive patients were on antihypertensive medication, 56.8% of them had uncontrolled BP. This study suggested that uncontrolled hypertension in patients with type 2 diabetes was positively associated with high BMI, pulse pressure, total cholesterol, and non-HDL cholesterol. This study showed that non-HDL cholesterol is a strong correlate of uncontrolled hypertension in patients with both type 2 diabetes and hypertriglyceridemia. Additionally, it was demonstrated that despite suggesting dual antihypertensive therapy as the first line by the latest evidence, more than 50% of patients with hypertension were still on monotherapy. Furthermore, the role of ineffective monotherapy, medical inertia, and patients' non-compliance in uncontrolled hypertension was illustrated. Identifying these predictors could be of great importance in that, it contributes to better strategic planning for tackling hypertension problems among high-risk patients.