|Year : 2020 | Volume
| Issue : 15 | Page : 20-23
Peripheral arterial disease and its predictors in type 2 diabetic patients in Nnewi, South-Eastern Nigeria
Ogonna Celestine Oguejiofor1, Chikezie Hart Onwukwe1, Chidiebele Malachy Ezeude1, Ejike Kenneth Okonkwo1, Justin Chibueze Nwalozie1, Charles Uzoma Odenigbo2, Charlotte Blanch Oguejiofor3
1 Endocrinology, Diabetes and Metabolism Unit, Department of Internal Medicine, Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria
2 Nephrology Unit, Department of Internal Medicine, Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria
3 Department of Obstetrics and Gynaecology, Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria
|Date of Submission||25-Jun-2019|
|Date of Acceptance||07-Jan-2020|
|Date of Web Publication||11-May-2020|
Dr. Chikezie Hart Onwukwe
The Endocrinology, Diabetes and Metabolism Unit, Department of Internal Medicine, Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State
Source of Support: None, Conflict of Interest: None
Background: Peripheral arterial disease (PAD) is a cause of foot disease in type 2 diabetes mellitus (T2DM) patients. Data on associated predictors of PAD in Nigerian T2DM patients are scanty, especially from Southeastern Nigeria. Objectives: The objective was to evaluate the prevalence and predictors of PAD in T2DM patients in Southeastern Nigeria. Materials and Methods: This is a cross-sectional study involving consenting T2DM patients at the Diabetes Clinic of the Nnamdi Azikiwe University Teaching Hospital, Nnewi, Southeastern Nigeria. History was obtained and physical examination was done on the study participants. Doppler ultrasound of the peripheral vessels was done using the Imex PD II Doppler device. Records of fasting plasma glucose on the day of Doppler assessment, glycated hemoglobin, fasting lipid profile, and electrocardiogram, done within the preceding 3 months, were obtained from the patients' clinic folders. PAD was defined as ankle–brachial pressure index <0.9 or >1.3. Data collection was done using researcher-administered study pro forma and analyzed using the Statistical Package for the Social Sciences version 20.P < 0.05 was considered statistically significant. Results: Of 100 T2DM patients (45 males and 55 females) recruited for the study, 74 (30 [40.5%] males and 44 [59.5%] females) had a complete data for analysis. The prevalence of PAD among the study participants was 59.5%. Significant predictors of PAD include the duration of DM, abdominal obesity, hypertension, triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C) levels. Conclusion: PAD is prevalent in T2DM patients in Southeastern Nigeria, with duration of DM, abdominal obesity, hypertension, TG, and HDL-C levels being significant predictors of PAD.
Keywords: Diabetes mellitus, peripheral arterial disease, predictors
|How to cite this article:|
Oguejiofor OC, Onwukwe CH, Ezeude CM, Okonkwo EK, Nwalozie JC, Odenigbo CU, Oguejiofor CB. Peripheral arterial disease and its predictors in type 2 diabetic patients in Nnewi, South-Eastern Nigeria. N Niger J Clin Res 2020;9:20-3
|How to cite this URL:|
Oguejiofor OC, Onwukwe CH, Ezeude CM, Okonkwo EK, Nwalozie JC, Odenigbo CU, Oguejiofor CB. Peripheral arterial disease and its predictors in type 2 diabetic patients in Nnewi, South-Eastern Nigeria. N Niger J Clin Res [serial online] 2020 [cited 2020 May 30];9:20-3. Available from: http://www.mdcan-uath.org/text.asp?2020/9/15/20/284086
| Introduction|| |
Peripheral arterial disease (PAD) is a major macrovascular complication of type 2 diabetes mellitus (T2DM) contributing to the development of diabetes mellitus (DM) foot syndrome. There is an increase in the morbidity and mortality in T2DM patients who develop gangrenous foot ulcerations. Fourteen to 24 percent of patients with T2DM who develop foot disease will require amputation.
PAD is prevalent in Nigerians with T2DM, but there are scanty data on the associated factors which predict PAD in T2DM patients in Southeastern Nigeria.
The objective was to evaluate the prevalence and predictors of PAD in T2DM patients in Southeastern Nigeria.
| Materials and Methods|| |
This is a cross-sectional observational study, involving consenting T2DM patients attending the Diabetes Clinic of the Nnamdi Azikiwe University Teaching Hospital, Nnewi, Southeastern Nigeria. They were recruited consecutively over a 3-month period. Patients with DM foot disease of any grade were excluded from this study. History obtained from the study participants included their biodata, duration of T2DM, medications used, and the presence of intermittent claudication or rest pain. Weight (in kg) was measured using a weighing balance with their footwear off and their height (in m) was measured with a stadiometer. The body mass index (BMI) in kilograms/square meter (kg/m2) was determined by dividing weight by the square of the height. Using a nonstretch tape, waist circumference (WC) was measured midway between the lower ribs and the highest point of the iliac crest, while hip circumference (HC) was measured at the widest diameter of the hip (in centimeters). The waist-to-hip ratio (WHR) was taken as the ratio of WC to HC. Blood pressure (BP) measurement was done on the right arm using an Accoson mercury sphygmomanometer with the patient in a sitting position.
Doppler ultrasound assessment of the peripheral vessels was done using the Imex PD II Doppler device with a 5 MHz Doppler probe with the patient in a supine position. The mercury sphygmomanometer BP cuff was applied to both arms to measure the brachial systolic BP (SBP) and just above each ankle to measure the dorsalis pedis and posterior tibial SBPs. The ankle–brachial pressure index (ABPI) of each lower extremity was determined by dividing the higher of the dorsalis pedis and posterior tibial SBPs by the higher of the brachial SBPs. Records of fasting plasma glucose done on the day of Doppler assessment and records of the following investigations done within the preceding 3-month glycated hemoglobin (HbA1c) and fasting lipid profile (total cholesterol, triglycerides [TGs], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol), were obtained from the patients' clinic folders.
Global obesity was defined as BMI ≥30 kg/m2, whereas overweight was defined as BMI of <25 kg/m2. Abdominal obesity was defined as WC >94 cm for males and >80 cm for females or WHR >0.90 for males and >0.85 for females. Hypertension was defined as BP >140/90 mmHg or the use of antihypertensive medications. Poor glycemic control was defined as HbA1c >6.5%. PAD was defined as ABPI <0.9 or >1.3.
Data collection was done using researcher-administered study pro forma. Data collected were analyzed using the Statistical Package for the Social Sciences version 20 (IBM Corporation, California, USA). Continuous variables were presented as mean ± standard deviation, whereas categorical variables were presented as proportions (in percent). Continuous variables were compared using Student's t-test. Binary logistic regression model was used to determine the predictors of peripheral arterial disease. P < 0.05 was considered statistically significant.
| Results|| |
A total of 100 T2DM patients (45 males and 55 females) were recruited for the study, however, 74 patients (30 [40.5%] males and 44 [59.5%] females) had complete data for the analysis. [Table 1] shows the clinical characteristics of the study patients. There was a statistically significant difference in BMI among male and female patients, with females having higher BMI than male patients (P = 0.03). Forty-four patients (16 males and 28 females) had PAD with a prevalence rate of 59.5%. Of these 44 patients, 11 (25%) had ABPI <0.9 with a PAD prevalence of 14.9% (11/74), whereas 33 (75%) had ABPI >1.3 with a PAD prevalence of 44.6% (33/74).
|Table 1: Clinical characteristics of type 2 diabetes mellitus patients by sex|
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[Table 2] shows the predictors of PAD in the study patients. T2DM duration, hypertension, abdominal obesity, triglyceride levels, and HDL-C levels were significant predictors of peripheral arterial disease. Poor glycemic control was not a significant predictor of peripheral arterial disease.
|Table 2: Predictors of peripheral arterial disease in type 2 diabetes mellitus patients|
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| Discussion|| |
This study showed that PAD was highly prevalent among T2DM patients in Southeastern Nigeria with prevalence as high as 59.5%. Similar high PAD prevalence rates among T2DM patients were also reported by Ikem et al. in Ile-Ife (55.4%), Ogbera et al. in Lagos (40%) (both from Southwestern Nigeria), and Mwebaze et al. in Uganda (39%). An earlier study by Oguejiofor et al. in Nnewi, Southeastern Nigeria, reported the PAD prevalence in T2DM patients with respect to age with the 50–59 years, 60–69 years, and ≥70 years age groups having PAD prevalence rates of 9.3%, 20.0%, and 26.3%, respectively. The overall PAD prevalence rate from their study was 12.5% although that study defined PAD with the sole criterion of ABPI <0.9. Our study defined PAD with dual criteria: ABPI <0.9 with prevalence rate of 14.9% (11/74) and >1.3 with prevalence rate of 44.6% (33/74), with overall PAD prevalence rate of 59.5%.
From our study, the duration of DM was a significant predictor of PAD in patients with T2DM. The Framingham Offspring Study showed a strong association between duration of DM and PAD on age- and sex-adjusted basis but not in multivariable models. The Bypass Angioplasty Revascularization Investigation in type 2 Diabetes (BARI 2D) trial showed that 303 (20.5%) out of 1479 T2DM patients developed incident PAD, and duration of DM had a significant relationship with the occurrence of PAD in these patients. The study by Ikem et al. also found a significant association between the duration of DM and the presence of PAD in Nigerians with DM. These reports are similar to our study which showed that the duration of DM was a significant predictor of PAD in T2DM patients. The development of macrovascular complications with the progression of DM possibly explains the significant relationship between DM duration and peripheral arterial disease. The study by Ogbera et al. did not find a significant relationship between the duration of DM and the occurrence of peripheral arterial disease. The reason for this disparity is unclear, but may be due to the sample size and patient recruitment criteria.
Our study showed that hypertension, with the highest odds ratio compared to other clinical variables, was a strong significant predictor of peripheral arterial disease in T2DM patients. The Edinburgh Artery Study found a significant association between hypertension and the presence of peripheral arterial disease. Ikem et al. also found a significant relationship between SBP and PAD in T2DM patients. These findings were similar to our study, in which hypertension was a significant predictor of PAD in T2DM patients, probably because of atherosclerotic macrovascular changes associated with chronic hypertension. The Rotterdam study showed that hypertension was a poor predictor of peripheral arterial disease. This dissimilarity with our study was probably based on a statistical model used in the Rotterdam Study that included both a categorical hypertension variable and an adjustment for the SBP level. The study participants in the Rotterdam study were elderly and this may have also contributed to hypertension not being a significant predictor of PAD in the study patients.
Our study also showed that abdominal obesity (by WC) was also a significant predictor of PAD in T2DM patients. A study by Vogt et al. showed that after adjustment for BMI, higher WHR was associated with significantly higher risk of peripheral arterial disease. Katsilambros et al. found that obesity by WHR, but not BMI or body fat percentage, was significantly associated with peripheral arterial disease in T2DM patients. These findings were similar to our study possibly due to the cardiovascular disease risk associated with central obesity. Ogbera et al. did not find any significant association between WC and PAD in T2DM patients probably as a result of sample size and patient recruitment criteria.
TGs and HDL-C were significant predictors of PAD in our study participants, with HDL-C being a stronger lipid predictor of PAD than TGs. Katsilambros et al. found that TGs and HDL-C were significantly associated with PAD in a cohort of study participants with T2DM. The speedwell prospective heart disease study also found that TGs and HDL-C were significantly associated with PAD. These reports were similar to our study finding probably due to the hypertriglyceridemia and low-HDL cholesterol levels associated with high cardiovascular risk in persons living with DM. The Physician's Health Follow-up Study (PHFS) found that the ratio of total cholesterol/HDL-C was the lipid measure most strongly associated with PAD, with patients in the highest quartile having 3.9 times the intermittent claudication risk of patients in the lowest quartile, while screening for other lipid fractions was judged to have little clinical usefulness beyond measurement of the total cholesterol/HDL-C ratio. The total cholesterol/HDL-C ratio was not determined in our study patients. The explanation for triglycerides not being significantly associated with PAD in the PHFS is unclear although this may be due to patient recruitment criteria.
Poor glycemic control defined as HbA1c of 6.5% and above was not a significant predictor of PAD in our study participants. This was similar to reports by Ogbera et al. and Chen et al. that found no significant difference in HbA1c levels among T2DM patients with PAD compared to similar patients without PAD., The sample size peculiarity in these studies may explain the similarity in the study findings. Other studies such as the Framingham Offspring Study and the BARI-2D trial showed a significant association between HbA1c and occurrence of PAD in the study participants with DM probably due to the progression of microvascular and macrovascular complications in DM patients with poor glycemic control., The Framingham Offspring Study and the BARI-2D trial were landmark studies involving a larger population of the study participants.
PAD is highly prevalent in T2DM patients in Southeastern Nigeria, and significant predictors for PAD include duration of DM, hypertension, abdominal obesity, triglyceride levels, and HDL-C levels.
The early diagnosis of DM and prompt evaluation to detect and manage these predictors of PAD will impact very positively on the prevalence of PAD in T2DM patients.
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Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2]