Saudi Journal of Obesity

ORIGINAL ARTICLES
Year
: 2019  |  Volume : 7  |  Issue : 1  |  Page : 21--28

Prevalence and predictors of dyslipidemia among hypertensive patients attending a secondary healthcare center in southwestern Nigeria


Ismaheel A Azeez1, Akinosun M Olubayo2, Kolawole A Adeyemo3,  
1 Department of Family Medicine, University College Hospital, Ibadan, Nigeria
2 Department of Chemical Pathology, College of Medicine, University of Ibadan, Ibadan, Nigeria
3 Department of Mathematics, Nigerian Police Academy Wudil, Kano, Nigeria

Correspondence Address:
Ismaheel A Azeez
University Department of Family Medicine, College Hospital Ibadan, Ibadan, Oyo
Nigeria

Abstract

Introduction: The prevalence of dyslipidemia is increasing globally with accompanied morbidities and mortalities. There is a paucity of data in Nigeria on the prevalence of dyslipidemia among adult hypertensive patients and this study aimed to assess the serum levels of lipids among hypertensive patients. Materials and Methods: This cross-sectional study of 354 hypertensive patients was conducted at the State Hospital, Oyo, Nigeria. The systematic sampling technique was used to recruit hypertensive patients, and the data were analyzed using SPSS software, version 23. Linear regressions were conducted to determine the predictors of dyslipidemia. Results: Three hundred fifty-four patients who met the criteria for recruitment were interviewed. The mean age of the respondents was 52.60 (SD ± 8.26) years. The prevalence of elevated low-density lipoprotein (LDL) was 43.6% (154), low high-density lipoprotein (HDL) in males was 25.4% (18/71), low HDL in females was 30.7% (87/283), elevated triglycerides was 1.4% (5), and elevated cholesterol was 29.9% (106). For every 1 unit increase in subscapularis skinfold, there was a statistically significant increase in triglyceride by about 0.036 units (95% CI = 0.032–0.040, P = 0.0001). For every 1 unit increase in triceps skinfold, there was a statistically significant increase in LDL by about 0.096 units (95% CI = 0.019–0.172, P = 0.013). For every 1 unit increase in hip circumference, there was a statistically significant decrease in HDL by about 0.007 units (95% CI = −0.009 to 0.013, P = 0.019). Conclusions: This study has facilitated the characterization of this population of hypertensive patients in terms of dyslipidemia, and this would be beneficial in their treatment and future care. Among these hypertensive patients, subscapularis, triceps skinfold thickness, and hip circumference predicted abnormal lipid profile.



How to cite this article:
Azeez IA, Olubayo AM, Adeyemo KA. Prevalence and predictors of dyslipidemia among hypertensive patients attending a secondary healthcare center in southwestern Nigeria.Saudi J Obesity 2019;7:21-28


How to cite this URL:
Azeez IA, Olubayo AM, Adeyemo KA. Prevalence and predictors of dyslipidemia among hypertensive patients attending a secondary healthcare center in southwestern Nigeria. Saudi J Obesity [serial online] 2019 [cited 2022 Dec 7 ];7:21-28
Available from: https://www.saudijobesity.com/text.asp?2019/7/1/21/353155


Full Text



 INTRODUCTION



The prevalence of dyslipidemia is increasing globally due to an increase in the consumption of meats and saturated fats. It is a major predisposing factor for stroke, ischemic heart diseases, and cancers. In a study conducted in Iraq among obese and nonobese patients at a teaching hospital, it was reported that cholesterol, triglycerides, and LDL were elevated, whereas HDL levels were reduced in obese compared with nonobese patients. Secondary generalization would be difficult because the study was hospital-based with a small sample size of 65 patients.[1] In another study conducted in Ibadan, Nigeria, the total cholesterol was raised, and the HDL was reduced. However, a small sample size of 55 would make secondary generalization difficult.[2] Wahab et al.[3] reported that obesity and overweight were associated with hyperlipidemia in a study conducted in Kaduna, Nigeria. Body fat mass rises when energy consumption exceeds energy used. In the long term, a positive energy equilibrium will result in excessive fat storage.[4] Its association with some diseases is due to the accumulation of adipose tissue in some parts of the body, which releases cytokines causing cellular damage and inflammation.[5] The lowering of glycemic indices of diets would lead to weight loss and improved lipid profile.[6] The burden of dyslipidemia on the healthcare system is increasing with accompanied morbidities, stress on the healthcare system, and economic loss. There is a paucity of data in Nigeria on the prevalence of serum lipid profiles among adult hypertensive patients, and adequate data on this condition would help in its comprehensive management. The objective of this study was to assess the serum levels of lipids among hypertensive patients attending a secondary healthcare center in Nigeria.

 MATERIALS AND METHODS



A cross-sectional study of hypertensive patients was conducted from March 2021 to August 2021 at the medical outpatients clinic of the State Hospital Oyo, a secondary healthcare center in Nigeria. The hospital had been a referral center for other hospitals in Oyo Federal Constituency, known for its comprehensive patients care and serving a wide geographical area of about 2 million population. The study involved 354 adults between 18 and 60 years with an established diagnosis of hypertension and already on treatment and follow-up for 6 months.

Definition of hypertensive patients

Hypertensive patients were those with systolic blood pressure of ≥140 mmHg and diastolic blood pressure of ≥90 mmHg diagnosed six months previously or patients on drugs for at least six months.[7]

Inclusion criteria were patients with systolic blood pressure of ≥140 mmHg and diastolic blood pressure of ≥90 mmHg diagnosed 6 months previously or patients on drugs for hypertension for at least 6 months. Exclusion criteria were patients with severe hypertension, for instance, systolic blood pressure of >180 mmHg and diastolic blood pressure of >110 mmHg who would need immediate evaluation.

The sample size was estimated using the formula:[8]

[INLINE:1]

Quoting n = minimum sample size; Zα = the standard normal deviate, usually set at 1.96, which corresponds to the 95% confidence level; p = the prevalence of hypertension to be 22.7% for Nigeria[9]; q = 1.0−p; and d = degree of accuracy desired usually set at 0.05.

[INLINE:2]

Considering 20% nonresponse:

q = 1/1−f, where q is the adjustment factor and f is the non response rate, if f = 20%.

q = 1/0.8 = 1.25

n = 1.25 × 270 = 337.5 = 338

For the purpose of this study, a minimum of 338 hypertensive patients were to be recruited. However, 354 patients were recruited to improve the power of the study.

Sampling techniques

The systematic sampling technique was used. About 80 patients with hypertension were seen per clinic that took place twice a week. Eight clinic days are run per month, which means 640 patients would be seen per month. Three thousand two hundred patients were expected to be seen in 5 months. The sampling interval was 9 (3200/354). The first patient was recruited by the simple random technique by the use of computer-generated random numbers. Random numbers within the range of the number of registered patients with hypertension were generated using the random number function of Microsoft Excel 2016. The numbers were sorted from smallest to largest and on each clinic day, nine patients with serial numbers corresponding to the random numbers generated were selected for recruitment. The consenting patients were numbered serially, and every ninth patient was recruited until the sample size of 354 (n) was completed.

Ethical consideration

The approval of the Ethical Review Committee of the Ministry of Health, Oyo State, Ibadan, Nigeria, was obtained. Written informed consents were obtained from eligible patients before the administration of questionnaires, examinations, and investigations. The study was conducted according to World Medical Association Helsinki’s declaration. The privacy and confidentiality of the respondents were guaranteed by the anonymity of the respondents.

The Committee’s reference number is AD 13/ 479/4023B.

Precautionary measures during COVID-19 pandemic

Respondents were educated about the COVID-19 pandemic. They were asked to use masks when coming to the clinic, and wash their hands before and after consultations. Respondents were asked if they have had symptoms of COVID-19 or came in contact with COVID-19 positive patients and suspected cases of COVID-19, and were counseled to go for tests. The principal investigator and the research assistants wore surgical masks or N95, surgical gloves, and ward coats to recruit patients. The laboratory scientists wore laboratory coats, surgical gloves, face shields, and surgical masks. The reasons for the tests were explained to the respondents. The personal data of the respondents and the blood samples were taken to measure serum lipid levels.

Anthropometric measurements

Waist circumference

This was measured by an inelastic measuring tape at the 0.1 cm. The patient was asked to stand erect with arms to the sides. The right lowest rib margin was located and marked with a pen. The iliac crest was palpated in the mid-axillary line and marked. The inelastic tape was then applied midway between the iliac crest and the lowest rib firmly around the umbilicus.

Hip circumference

This was measured by an inelastic measuring tape at the 0.1 cm. The patient was asked to stand erect with arms to the sides and legs together. The measurement was taken at the point with the highest circumference at the buttocks with the tape held horizontally touching the skin.

Subscapular

The subscapular skinfold was measured at the lower angle of the right scapula. The skinfold was acquired at 450 about 2 cm below the lowest tip of the shoulder blade, almost parallel to the inside angle of the shoulder blade itself.

Triceps

The triceps skinfold was measured at the upper arm mid-point mark on the posterior surface of the right upper arm. It is the perpendicular skinfold that is acquired mid-way between the top portion of the shoulder and the elbow.

Biceps

This consists of a perpendicular skinfold parallel to the arm located over the biceps midway between the shoulder and the elbow.

Supra-iliac

The skinfold was located between the upper portion of the hip bone and the bony portion of the same hipbone along the lower right of the body above the iliac crest in the mid-axillary line.

Height

The heights of the respondents were measured using a calibrated wooden stadiometer. The heights were measured to the nearest 0.01 m. The stadiometer was placed on a flat surface. The respondents were asked to remove their shoes, and their heels were positioned against the wall. The respondents were also asked to remove their headwear, and the hair was flattened temporarily with a hard-flat surface making it perpendicular to the wall. Zero error was adjusted after each respondent for accuracy.

Weight

The patient was asked to have a 12-h fast and an emptied bladder. The weight was measured to the nearest 0.1 kg using a weighing scale (Elgil Medical, UK) with the respondents wearing only very light body clothing and barefooted. The participant was asked to stand on the platform looking straight but still. After taking the first measurement, the procedure was repeated and the average was recorded.

Laboratory procedures for fasting lipid profiles

Principles

Triglyceride

The enzymatic method of Bucolo and David (1973) cited by Kawano et al.[10] was used. Triglycerides are hydrolyzed by lipases to glycerol and fatty acids. The glycerol is oxidized to dihydroxyacetone phosphate and hydrogen peroxide, eventually, further procedures produce quinoneimine (chromogen). The higher the degree of absorbance of the chromogen, the higher the concentration of the triglyceride. Normal triglyceride was <3.88 mmol/L and elevated triglyceride was ≥3.88 mmol/L.

Total cholesterol

Total cholesterol was determined using the enzymatic method of Allain et al. (1974) cited by Saliu et al.[11] Cholesterol ester hydrolase hydrolyzes cholesterol esters to free cholesterol, which is then oxidized by cholesterol oxidase to cholest-4-en-3-one. There was the production of hydrogen peroxide that couples with 4-aminopyrine and phenol to produce chromogen. The color intensity is proportional to cholesterol concentration. Normal cholesterol was <5.17 mmol/L and elevated cholesterol was ≥ 5.17 mmol/L.

High-density lipoprotein

The precipitation method by Assmann et al. (1983) cited by Di Angelantonio et al.[12] was used. The addition of phosphotungstic acid in the presence of magnesium ion precipitates LDL, VLDL, and chylomicrons from plasma leaving HDL in the supernate. The cholesterol in the HDL is estimated using the method of Allain et al. (1974). For females, the normal HDL was ≥1.29 mmol/L and low HDL was <1.29 mmol/L. For males, the normal HDL was ≥1.03 mmol/L and low HDL was <1.03 mmol/L.

Low-density lipoproteins cholesterol determination

LDL was calculated by using Friedewald formula (Friedwald et al. 1972) cited by Kimenya et al.[13]

LDL cholesterol (mg/dL) = Total cholesterol (mg/dL) − (triglyceride/5 (mg/dL) + HDL-C (mg/dL)). The normal LDL was <2.59 mmol/L and elevated LDL was ≥ 2.59 mmol/L.

 RESULTS



Three hundred and fifty-four (354) patients who met the criteria for recruitment were interviewed. The mean age of the respondents was 52.60 (SD ± 8.26) years. All patients had completed serum lipids results.

Distribution of fasting lipids

The prevalence of elevated LDL was 43.6% (154/354), prevalence of low HDL in males was 25.4% (18/71), prevalence of low HDL in females was 30.7% (87/283), prevalence of elevated triglycerides was 1.4% (5), and prevalence of elevated cholesterol was 29.9% (106) [Table 1].{Table 1}

Relationships of total cholesterol and triglyceride with selected variables

As shown in [Table 2], there was no relationship between body mass index (BMI) and cholesterol (P = 0.773). Also, for age, there was no association with cholesterol (P = 0.643).{Table 2}

Relationship of serum lipids with skinfold measurements

As shown in [Table 3], the relationship of supra-iliac skinfold with triglyceride was positive, weak in strength, and statistically significant (P = 0.013). However, for LDL, there was no association with supra-iliac skinfold measurements (P = 0.061).{Table 3}

Linear regression for triglyceride on significant variables

As shown in [Table 4], for every 1 unit increase in subscapularis skinfold, there was a statistically significant increase in triglyceride by about 0.036 units (95% CI = 0.032–0.040, P = 0.0001). For every 1 unit increase in triceps skinfold measurements, there was a statistically significant increase in triglyceride by about 0.015 units (95% CI = 0.003–0.026, P = 0.01).{Table 4}

Relationship of LDL and HDL with selected variables

There was no relationship between waist circumference and LDL (P = 0.871) as shown in [Table 5]. For age, there was no association with LDL (P = 0.231).{Table 5}

The relationship between the hip circumference and HDL was negative, weak in strength, and statistically significant (P = 0.019).

Linear regression for LDL on significant variables

As shown in [Table 6], for every 1 unit increase in triceps skinfold, there was a statistically significant increase in LDL by about 0.096 units (95% CI = 0.019–0.172, P = 0.013).{Table 6}

Linear regression for HDL on significant variables

As shown in [Table 7], for every 1 unit increase in hip circumference, there was a statistically significant decrease in HDL by about 0.007 units (95% CI = −0.009 to 0.013, P = 0.019).{Table 7}

 DISCUSSION



The increasing prevalence of dyslipidemia is contributory to the burden of cardiovascular diseases and is of public health concern. The relationships of LDL with supra-iliac, triceps, and biceps skinfold measurements were explored in this study. The predictors of reductions in LDL were reductions in triceps skinfold measurements. The relationships of BMI and hip circumference with HDL were negative and weak. The higher the BMI and hip circumference, the lower the HDL and the predictor of an increase in HDL was a reduction in hip circumference. The predictors of triglycerides were triceps and supa-iliac skinfold measurements. A Kenyan study showed a high prevalence of dyslipidemia in patients with type 2 diabetes mellitus, and employment status, BMI, fasting blood glucose, and physical activity were associated with dyslipidemia.[14] This was similar to the results of this study that showed elevated prevalence of dyslipidemia which could be due to its conduct in hypertensive patients. The findings of this study were contrary to the results of another study in Nigeria, which reported that there was no correlation between dyslipidemia and anthropometric measurements.[15] However, waist circumference correlated strongly with systolic and diastolic blood pressures. Obesity was associated with hypercholesterolemia according to the findings of Wahab et al.[3] The higher the degree of obesity, the higher the cholesterol levels.[3] The prevalence of hypercholesterolemia was high (29.9%) in this study. This was similar to what was reported by Olabisi et al. who used a sample size of 55 patients for their study in Ibadan, which was relatively low.[2]

Age greater than 60 years and physical activity were found to be independent predictors of dyslipidemia according to Ayoade et al. Also, 20.8% had hypertriglyceridemia and 60% had dyslipidemia.[16] However, the prevalence of hypertriglyceridemia in this study was low (1.4%) and LDL had the highest prevalence of 43.6%. In a study of geriatric hypertensive patients in a rural community in Nigeria, the prevalence of abdominal obesity and the prevalence of abnormal HDL was high. Although the sample size of 122 was inadequate, there was a need to health educate those hypertensive patients in the rural communities.[17] The findings were similar to the findings of this study, which showed a high prevalence of abnormality of HDL due to its conduct among hypertensive patients.

In another study, the prevalence of dyslipidemia was found to be 40.2% and there was no predictive variable for dyslipidemia that might be due to an inadequate sample size of 206. However, sedentary time was found to be a risk factor for obesity.[18] Mixed dyslipidemia of high triglyceride and LDL cholesterol prevalence of 41% was recorded in another study in Kaduna, Nigeria, in contrast to the findings of this study.[19] In a study to assess the prevalence of dyslipidemia among University workers, cholesterol, triglycerides, and LDL were elevated, whereas high alcohol intake was associated with dyslipidemia. Counseling for diets and regular exercise would be very important in this population of civil servants.[20] Overweight, obesity, and hyperlipidemia were the predictors of hypertension among hypertensive patients according to the outcome of a review by Olabisi et al.[21] In another study, lipid levels were found to be higher in females except for triglycerides that were higher in males. The rural study showed that the risk of cardiovascular diseases was higher in females than males.[22] The pattern of dyslipidemia among patients with type 2 diabetes mellitus in a study conducted in Jos, Nigeria, showed elevated LDL, total cholesterol, and triglycerides as compared with a controlled group without diabetes and hypertension.[23] The elevated levels of the lipid parameters were similar to the results of this study except for the prevalence of triglycerides levels, which were low.

To evaluate the association of gender and dyslipidemia, Vij et al.[24] conducted a study in India. The mean values of serum lipids and glucose were found to be higher in females than males. However, the mean value of HDL was also higher in females.[24] Akinwusi et al.[25] conducted another study in a rural community in Osun, Nigeria, and found elevated serum lipid profiles. Hypercholesterolemia was 17.8%, 13.5% had elevated LDL, 38.2% had hypertriglyceridemia, and 49.8% had low HDL values.[25] This was in contrast to the findings of this study in which the prevalence of triglycerides was lower. To assess lipid profiles in patients with type 2 diabetes mellitus in another rural community, 50.4% were reported to have dyslipidemia. The prevalence could be higher in patients with diabetes mellitus. However, a sample size of 113 used might be inadequate to achieve the objectives of the study.[26] Hyperlipidemia could lead to macrovascular disease, hence the need to screen patients with type 2 diabetes mellitus so that those who have the disease could be treated early.[26],[27]

In another study to compare the lipid profiles in patients with obese type 2 diabetes mellitus and nonobese type 2 diabetes mellitus, serum levels of cholesterol, triglycerides, and LDL were elevated by more than 50%, whereas HDL was reduced in more than 38%. Although there was no significant change in total cholesterol, this study showed that obesity was associated with type 2 diabetes mellitus.[28] Also in another study, the prevalence of elevated LDL, triglyceride, cholesterol, and reduced HDL were recorded as 43.8, 23.7, 40.6, and 41.9, respectively. Dyslipidemia was associated with hypertension, BMI, age, and longer duration of diabetes mellitus.[29] In the assessment of the impact of age, sex, and diabetes mellitus on serum lipid profiles, it was reported that patients above 45 years were at greater risk of developing dyslipidemia. Females had higher levels of HDL and triglycerides than males. Men were less prone to dyslipidemia than women and patients with diabetes had an increased risk of developing abnormal lipid levels.[30] In this study the prevalence of abnormal HDL was higher in females than males. To explore the prevalence and pattern of dyslipidemia in patients with stroke, reduced HDL was found to be the major risk factor. Dyslipidemia was also reported to be a major risk factor in ischemic stroke compared with hemorrhagic stroke.[31] A case-control study showed elevated triglycerides, low HDL, and slightly raised LDL in a study carried out in Swat, Pakistan. The prevalence of dyslipidemia and hyperglycemia was higher in patients with diabetes compared with controls, whereas there was no significant difference in blood pressure between patients with diabetes and those without diabetes mellitus.[32] Harsha et al.[33] reported no significant associations between skinfold measurements and lipid profile. This might be due to the sample size of 50 used in their study.[33] This study in contrast showed that triceps and subscapularis skinfold measurements were predictors of triglycerides, whereas triceps skinfold measurements were predictors of LDL. However, hip circumference measurements were predictors of HDL.

 CONCLUSIONS



This study has helped to characterize this population of hypertensive patients in terms of dyslipidemia, and this would be beneficial in their management and planning of future care. Among these hypertensive patients, subscapularis, triceps skinfold thickness, and hip circumference predicted dyslipidemia. The prevalence of dyslipidemia was high in this population of hypertensive patients increasing the risk of cardiovascular diseases although the prevalence of triglyceride was relatively low. Patients have to be counseled on the need to reduce consumption of saturated fats and meat to curb the increasing prevalence of dyslipidemia.

Knowledge added to science

The predictors of LDL were triceps skinfold measurements; the predictors of triglycerides were triceps and subscapularis skinfold measurements; and the predictors of HDL were hip circumference measurements. Skinfold measurements could therefore be used to assess obesity to complement to BMI and waist-to-hip ratio.

Limitations of the study

The study was a hospital-based cross-sectional and the results obtained might not be a true reflection of what obtains in the community. Besides, causal relationships could not be established, hence there is a need for interventional studies. However, the study had given insight into the high prevalence of dyslipidemia in the population studied.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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