https://orcid.org/0000-0002-6855-2827
Figures
Abstract
Background
One of the major risk factors for cardiovascular disease is atherogenic dyslipidemia. There was, however, little information available in Ethiopia. Therefore, the purpose of this study was to estimate the prevalence of atherogenic dyslipidemia and related risk factors in Northeast Ethiopian hypertension patients.
Materials and methods
A systematic random sampling technique was used to perform a cross-sectional study at an institution with 384 chosen participants. A structured questionnaire was used to collect the socio-demographic, anthropometric, lifestyle, and clinical characteristics of the respondents. Student’s t-test, Mann-Whitney test, and Pearson’s Chi-square test were employed to compare groups based on the type of data. Furthermore, Bivariate and multivariable logistic regression analyses were performed to identify factors independently associated with dyslipidemia. Crude and adjusted odds ratios and their corresponding 95% Confidence Intervals (CI) were computed. In all cases, statistical significance was declared at p <0.05.
Results
The majority (93.2%; 95%CI: 90.6–95.6) of patients had at least one atherogenic dyslipidemia. The prevalence of elevated total cholesterol (TC), elevated triglyceride (TG), raised low-density lipoprotein cholesterol (LDL-c), and reduced high-density lipoprotein cholesterol (HDL-c) were 47.7%, 50.3%, 44.3%, and 59.6%, respectively. Being≥ 40 years were at higher risk for having elevated levels of TC (AOR: 3.22, 95% CI: 2.40–4.32), TG (AOR: 2.30, 95% CI: 1.61–3.79), and LDL-c (AOR: 4.68, 95% CI: 2.0–10.95) than those who were below 40years. Obese participants were more likely to have high concentrations of TC (AOR: 2.57, 95%CI: 2.10–3.22), LDL-c (AOR: 3.13, 95% CI: 1.97–5.10), HDL-c (AOR: 2.71, 95% CI: 1.77–4.58), and TG (AOR: 2.23, 95%CI: 1.79–4.16).
Citation: Mohammed O, Alemayehu E, Ebrahim E, Fiseha M, Gedefie A, Ali A, et al. (2023) Atherogenic dyslipidemia and associated risk factors among hypertensive patients of five health facilities in Northeast Ethiopia. PLoS ONE 18(2): e0277185. https://doi.org/10.1371/journal.pone.0277185
Editor: Paolo Magni, Università degli Studi di Milano, ITALY
Received: June 25, 2022; Accepted: October 21, 2022; Published: February 14, 2023
Copyright: © 2023 Mohammed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting information files.
Funding: The authors received no specific funding for this work.
Competing interests: The authors declare that they have no potential competing interests.
Introduction
Globally, it is estimated that one billion adults live with hypertension; this figure is predicted to be more than 1.5 billion by the year 2025. Furthermore, at least 45% of fatalities from heart disease and 51% of deaths from stroke were caused by hypertension [1]. Due to inadequate levels of therapy and management of hypertension in Africa, the high burden of hypertension is the main cause of mortality and morbidity linked with cardiovascular disorders globally [2–5]. In Ethiopia, hypertension is one of the most common public health burdens. The pooled prevalence of hypertension in the Ethiopian population was calculated to be 19.6 percent [6].
More than half of the 17.4 million fatalities per year that occur worldwide are caused by cardiovascular illnesses, which are connected to hypertension. The research suggests that responsible authorities should pay more attention to the cardiovascular health of African populations living in both rural and urban areas [7, 8]. According to the etiology and prognosis of atherosclerosis and cardiovascular disease (CVD), hypertension and atherogenic dyslipidemia frequently coexist [9–12]. One of the primary risk factors for the development of atherosclerosis is atherogenic dyslipidemia. The prevalence of cardiovascular disorders has increased as a result of the expansion of atherosclerosis. Thus, it is clear that the frequent co-occurrence of hypertension, atherosclerotic dyslipidemia, and other metabolic abnormalities in patients increases the risk of heart failure and CVD-related morbidity and death [13–16].
Currently, CVD is one of the most common causes of death worldwide and is on the rise [17]. Compared to people with normal lipid levels, those with atherogenic dyslipidemia are more likely to develop CVD [18]. High levels of total cholesterol (TC), hypertriglyceridemia, low-density lipoprotein cholesterol (LDL-c), lower HDL-c, and an increased atherogenic index TC/HDL-c ratio are all indicators of atherogenic dyslipidemia [19–22]. Atherosclerosis, which is known as the main risk factor for stroke, peripheral vascular disease, and coronary heart disease (CHD), is made more likely by elevated blood levels of certain lipids [23]. LDL-c may have an impact on the onset of atherosclerosis [22]. On the other hand, HDL-c plays a role in the reverse transport of cholesterol, which decreases the risk of atherosclerotic CVD [22, 24].
Patients with coexisting cardiovascular risk factors, such as hypertension, have a substantially greater prevalence of dyslipidemia [25, 26]. A number of risk factors were linked to dyslipidemia among hypertension patients, according to empirical data from earlier literature. These risk variables included sedentary behavior, age, gender, obesity, smoking, diabetes, and a poor diet of fruits and vegetables [27, 28]. Although non-healthy food and people’s behaviors are linked to roughly 80% of dyslipidemia [29], this percentage is still high. In addition, Kifle Z et al. and Hirigo A et al., respectively, observed high rates of dyslipidemia among Ethiopian hypertensive patients (48.4% and 90.8%) [27, 28].
Evidence suggested that the rising prevalence of atherogenic dyslipidemia and hypertension in patients may significantly deteriorate their state of health [10, 12, 30, 31]. In the majority of developing nations, including Ethiopia, CVD-related diseases and hypertension have recently become major public health issues [3, 4, 27]. There were few data on the prevalence of dyslipidemia and related variables in hypertension patients in Ethiopia, despite its high prevalence and related complication in this population. To our knowledge, we found only a few published studies that were conducted in one healthcare setting. As a result, they might not be representative of the general public. The current study’s objective was to evaluate atherogenic dyslipidemia and the factors that contribute to it among hypertensive patients at five healthcare facilities in northeast Ethiopia.
Materials and methods
Study design, setting and period
The current institution-based cross-sectional study was conducted at the selected hospitals in Dessie town from June to October 2021. The town has a cold temperature and is located on a mountain crest. Its entire area is 15.08 km2, and its distance from Addis Ababa, the county headquarters, and Bahir Dar, the capital of the Amhara regional state, respectively, is 401 km and 471 km. Eight health facilities, three private general hospitals, five higher private clinics, one general hospital, one comprehensive specialized hospital, and one general hospital are all located in Dessie town and provide medical services to the surrounding areas [32]. For the purpose of this study five (namely, Dessie comprehensive specialized hospital, Borumeda general hospital, Selam general hospital, Ethio general hospitals, and Bati general hospitals) health facilities that provide chronic diseases services were selected.
Study population and legibility criteria
Patients with hypertension who visited the chronic department of particular hospitals during the study period were included. Based on a single population proportion calculation and a 48.4% overall prevalence of dyslipidemia in hypertension patients, the sample size was determined [27]. With a 95% confidence level, the expected margin of error (d) was calculated at a level of 0.05. Thus, the calculated sample size was 384. The overall sample size was appropriately distributed based on the number of registered hypertension patients in each healthcare setting because the data were gathered from five distinct healthcare facilities. A methodical random sampling strategy was used to choose the respondents. All volunteer hypertensive patients age ≥18years-old who had a regular follow-up were eligible in the 1study. However, physiological and pathological factors that could alter serum lipid profiles, such as pregnancy, taking lipid-altering drugs, and antihyperlipidemic medications, were excluded because the study was designed to assess dyslipidemia. Moreover, critically ill and those with mental problems and unable to communicate were excluded from the study.
Data collection and quality control
Data were collected through a structured, validated, and pretested face-to-face interviewer-administered questionnaire. The questionnaire contained information on socio-demographics, history of co-morbidity, the habit of physical exercise, behavioral habits (alcohol consumption and smoking), etc. Two well-trained data collectors (BSc nurses) were recruited for each health facility. They were given training for two days on the method of extracting the needed information, how to fill the information on a structured questionnaire, and the ethical aspect of approaching the participants as well as the aim of the study and the contents of the instruments. The data collection material was pre-tested on 10% of the sample size to check completeness, consistency, and applicability and was modified accordingly. The researchers were making spot-checks of at least 5 questionnaires per day. Reviewing the completed questionnaire by the data collectors ensures completeness and consistency of the information that was collected. Quality control was carried out during the pre-analytical, analytical stages, and post-analytical phases. Furthermore, patient samples were evaluated alongside analytical stage quality control checks, which included quality control materials (Normal, Low, and High) to detect if analytic errors had occurred.
Anthropometric measurement and biochemical analysis
Following a standardized protocol, weight, and height were measured by trained collectors. Standing heights were taken without shoes to the closest 0.1 cm using well-situated stadiometers. The weights were measured to the closest 0.1 kg using a digital balance. Weights were measured without heavy clothes and shoes, while heights were measured without shoes to get an accurate measurement. After 5 minutes of rest, blood pressure was checked in triplicate, with subsequent readings taken 5 minutes apart. Additionally, body mass index (BMI) was calculated as the product of weight (kg) and height (meters), squared (kg/m2). Participants with a BMI lower than 18.5 kg/m2 were considered as underweight; between 18.5 and 24.9 kg/m2 as normal; between 25.0 and 29.9 kg/m2 as overweight and 30.0 kg/m2 and above as obese [33]. Waist circumference (WC) was measured at the level of the iliac crest and the level of the umbilicus in cm to evaluate abdominal obesity, and raised WC was defined as ≥94 cm for men and ≥80 cm for women [34]. The average values from each set of three duplicate anthropometric measurements were utilized to conduct the analysis.
After obtaining consent, around 5 ml of venous blood sample was collected after overnight fasting for TG, HDL-c, LDL-c, and TC tests. The blood sample was clotted for 30 minutes. Then, the serum sample was separated from the Nunc tube following centrifuged for 5 minutes at 4000 revolutions per minute. Lipid profile parameters were analyzed with a fully automated clinical chemistry analyzer using the direct endpoint enzymatic process. All samples were analyzed within 24 hours with the same analyzer to minimize assay variation. Before sample analysis, the machine was checked using controls and blank on a daily basis. The cut-offs for abnormal serum lipid levels were: ≥200 mg/dL for total cholesterol (TC), for triglyceride (TG) concentrations of ≥150 mg/dL, for (LDL-c)>130 mg/dL, and HDL-c <40 mg/dL based on the National Cholesterol Education Program (NCEP) reference limits. According to NCEP the applied the cut-off value for TC/HDL-c ratio was ≥5. Hence, according to the NCEP guidelines, individuals should have at least one of the lipid parameters that become abnormal to be categorized under the presence of dyslipidemia [22].
Data analysis
The statistical analysis was performed using the SPSS version 23 statistics package for social sciences. Data were summarized as means/median ± standard deviation and proportion (percentages) for continuous and qualitative data, respectively. Comparisons between groups were done using Student’s t-test and X2, respectively, for continuous and categorical data respectively. Besides, the normality of the continuous variables was checked and the Mann-Whitney test was used for skewed distribution. Furthermore, bivariate and multivariable logistic regression analyses were performed to identify factors independently associated with dyslipidemia. Crude and adjusted odds ratios and their corresponding 95% Confidence Intervals (CI) were computed. In all cases, statistical significance was declared at p <0.05.
Ethics approval and consent to participate
The study was approved by the Institutional Review Board of Wollo University, College of Medicine and Health Sciences, and ethical clearance was obtained. The appropriate health facilities received official letters of collaboration, and consent was acquired. Prior to collecting any data, each study participant gave their written informed consent after being fully aware of the study’s protocols and the involvement was completely voluntary.
Results
Prevalence of dyslipidemia according to socio-demographic characteristics of study participant’s
A total of 384 respondents were included in the current study with a 100% response rate. Among them, 202 (52.6%) were men. More than two-thirds (67.2%) of the hypertensive individuals were 40 years and above, while 32.8% were in the age range of 18–39 years with a mean age of 46.5±12.7 years. Similarly, more than half 213(55.5%) of the hypertensive peoples were permanent residents of urban areas. Of the total hypertensive individuals, the highest of prevalence lipid abnormalities was seen for reduced HDL-C level (59.6%), followed by elevated triglycerides (50.3%), elevated total cholesterol (47.7%), and elevated LDL-C (44.3%) in both sexes. Likewise, the magnitude of all serum lipid profile derangements was significantly different across gender and age groups (P<0.05). A higher percentage of female hypertensive individuals had elevated lipid profiles (P<0.05). Furthermore, the urban residence participants had significantly higher serum lipid abnormalities of 122(57.3%), 113(55.0%), 119(55.9%), and 133(62.4%) for TC, TG, LDL-c, and HDL-c respectively (P <0.05) (Table 1).
Magnitude of dyslipidemia according to comorbidity and lifestyle practices of participants
Regarding the respondents’ lifestyle, 287(74.7%) and 311(81.0%) reported that they did not regularly eat fruits/vegetables. While 139 people (36.2%) and 34 (8.9%) had experienced overweight and obesity, respectively, half of the hypertensive individuals (51.6%) had maintained normal body weight. Additionally, 319 hypertensive patients (83.1%) reported chewing tobacco, 60 (15.6%) claimed now smoking cigarettes and 67 participants (17.4%) reported currently drinking alcohol. Only 239 (62.2%) of the individuals consistently took their antihypertensive medications.
Interestingly, among those hypertensive patients who engaged in sedentary physical activity, the prevalence of atherogenic dyslipidemia was highest for TC, TG, LDL-c, and HDL-c at 54.0%, 57.9%, 52.1%, and 66.9%, respectively (P<0.05). Additionally, the prevalence of atherogenic dyslipidemia varied from 76.5% to 91.2%, among people who were overweight or obese, while it ranged from 26.3 to 51.0% in those with normal body weight (p <0.005). Furthermore, a raised waist circumference, long-term hypertension, and familial history of hypercholesterolemia were all consistently associated with low HDL-c (p <0.005). Similarly, among those who reported a familial history of hypercholesterolemia, TC, TG, LDL-c, and HDL-c lipid derangements were prevalent in 80.8%, 74.4%, 69.2%, and 84.6% of cases, respectively. Patients with DM co-morbidities had the highest prevalence of elevated LDL-c (72.4%) with a P-value<0.005). Additionally, as shown in the table below, atherogenic dyslipidemia varied from 66.0% for LDL-c to 76.7% for HDL-cholesterol (P<0.05) among people with hypertension for at least 10 years (Table 2).
Female hypertensive patients had significantly higher mean serum concentrations of TC, LDL-c, HDL-c, and TG (p-value<0.05). Besides, the derived mean ±standard deviation (SD) of the TC, LDL-c, and HDL-c and the median value of TG were 198.6±54.2, 123.3±41.2, 40.2±10.4, 170±109.7 for combined sexes respectively (Table 3).
Co-occurrence of the lipid abnormalities and raised TC/HDL-c ratio
In the study subjects, the combined elevation of TC+TG was 68 (37.4%), 50 (24.8%) for males, and 50 (24.8%) for females. Similarly, the overall prevalence of elevated TC+LDL-c was 76 (37.6 percent) for males and 73 (40.1%) for female hypertensive patients. Besides, the prevalence of three lipid profile derangements (TC+TG+LDL-c) in a single individual was 89 (23.2%), while 67 (17.4%) of the hypertensive subjects had exhibited abnormalities in all four serum lipids. The present study revealed that the majority (93.2%; 95%CI: 90.6–95.6) of the hypertensive patients had experienced dyslipidemia in at least one lipid profile that is compatible with the diagnosis of dyslipidemia. Moreover, this work noted that more than half (52.3%) of the hypertensive patients had a raised TC/HDL-c ratio (Table 4).
Predictors of dyslipidemia among hypertensive patients
In the bivariate analysis model, many predictors such as sex, age, marital status, occupation, taking antihypertensive medicine, duration of hypertension, family history of hypercholesterolemia, BMI, current cigarette smoking, and comorbidity were recruited as risk factors for most of the lipid profile derangements (P-value<0.05). Participants whose age ≥ 40 years were at higher risk for having elevated levels of TC and TG with a value of (AOR: 3.22, 95% CI: 2.40–4.32, P-value<0.001), and (AOR: 2.30, 95% CI: 1.21–3.79, P-value = 0.04) than those who were below 40 years of age respectively. Regarding sex, female hypertensive individuals are at higher risk for having elevated concentrations of TC (AOR: 2.02, 95% CI: 1.26–3.70, P-value = 0.02), and TG (AOR: 1.52, 95% CI: 1.02–1.92, P-value = 0.005) than male counterparts. Moreover, participants who had sedentary lifestyles are at more risk for having elevated atherogenic TC and TG levels (AOR: 2.01, 95% CI: 1.52–2.89, P-value = 0.03), and TG (AOR: 1.94, 95% CI: 1.25–2.69, P-value = 0.04), respectively. Additionally, obese people are more likely to have high concentrations of TC (AOR: 2.57, 95%CI: 1.97–3.22, P-value = 0.01) and TG (AOR: 2.23, 95%CI: 1.29–4.16, P-value = 0.03). Likewise, multivariate analysis revealed that current cigarette smoking and the habit of not eating fruits and vegetables were significantly associated with elevated TC levels but not with elevated TG levels (Table 5).
The odds of aberrant LDL-c and HDL-c were also 4.68 (AOR: 4.68, 95%CI: 2.0–10.95) and 1.22 (AOR: 1.22, 95%CI: 0.58–2.56) times higher among patients aged 40 years and older, respectively, compared to subjects aged below 40 years, in the multivariable logistic regression model. Participants with a history of current smoking had 1.75 (AOR: 1.75, 95%CI: 1.19–2.43) and 1.8 (AOR: 1.81, 1.41–1.60) times the odds of developing LDL-c and HDL-c than non-smokers, respectively. Those with increased waist circumference were more likely than those with normal waist circumference to have aberrant LDL-c and HDL-c levels (AOR: 1.64, 95%CI: 0.95–2.83) and (AOR: 2.21, 95%CI: 1.28–3.89), respectively. Besides, sedentary lifestyles were associated with 2.5 (AOR: 2.48, 95%CI: 1.18–3.79) and 2.2 (AOR: 2.24, 95%CI: 1.24–4.04) times greater risks of atherogenic LDL-c and HDL-c abnormalities, respectively. Hypertensive patients with DM comorbidity were more likely than those without to have abnormal LDL-c and HDL-c levels by 2.58 (AOR: 2.58, 95%CI: 1.59–4.21) and 2.2 (AOR: 2.20, 95%CI: 1.25–3.74) times, respectively. In addition, those who reported having a family history of hypercholesterolemia had a 1.49 (AOR: 1.49, 95%CI: 1.07–1.91) and 1.90 (AOR: 1.90, 95%CI: 1.31–2.52) times higher risk of LDL-c and HDL-c abnormalities, respectively, compared to those who did not report a family history of hypercholesterolemia (Table 6).
Discussion
Dyslipidemia was made worse by hypertension’s impact on the blood lipid metabolism. Blood lipid concentrations and blood pressure were linked to and impacted by each other, and atherogenic dyslipidemia increased blood pressure variability. In emerging nations, atherogenic dyslipidemia, which is becoming more prevalent, is a significant risk factor for CVD emergence [9, 10]. Majority (93.2%) of the hypertensive patients in this study had at least one lipid profile with atherogenic dyslipidemia, and 17.4% to 38.8% had dyslipidemia with two or more lipid profile derangements. In line with the present study a high prevalence dyslipidemia were reported in Southern part of Ethiopia (90.8%) [28], Lithuania (89.7%) [35], South Africa (85.0%) [36], Poland (77.2%) [37] and Indonesia (79.5%) [38]. However, this finding is higher than previous studies done in Gojjam Ethiopia (48.4%) [27], Mekelle Ethiopia (66.7%) [39], Harar Ethiopia (34.8%) [40], South Africa (67.3%) [41], Uganda (63.3%) [42], Palestine (66.4%) [43] and Iran (30.0%) [44]. In the current study, we recruited only hypertensive patients who were at higher risk for dyslipidemia than general populations. Moreover, this difference might be due to variation in the lifestyles and behavioral characteristics of respondents, sample size, method, stage of urbanization, cut-off values, and socioeconomic status.
Abnormally reduced HDL-c was the most prevalent (59.6%) component of dyslipidemia followed by elevated TG levels (50.3%), which is in line with previous studies [27, 28, 45–48]. Low HDL-c has been linked to atherogenesis and the development of cardiovascular disease, according to data. Most of the patients in our study were at high risk of developing CVD. Besides, the prevalence of elevated LDL-c was 44.3%, which was consistent with earlier studies done in Mekelle, Ethiopia (49.5%) [39], India (47.8%) [49], Iran (50.0%) [50], Thailand (56.5%) [51], Uganda (60.9%) [52], Ghana (61.0%) [53], Senegal (66.3%) [54] and Jordan (74.9%) [55]. The current finding, however, was greater than earlier studies with a similar focus that were conducted in Gojjam (16.1%) [27], and in other regions of Ethiopia (14.1%) [56], and lower than the finding from Southern Ethiopia (60.9%) [28]. The differences in the cutoffs, methodology, respondents’ lifestyle, behavioral patterns, and the socioeconomic position may be to blame for these disparities in the results.
The prevalence of elevated total cholesterol (47.7%) is comparable to studies conducted in other African nations [52–54, 56, 57], but greater than those conducted in Harar Ethiopia (33.7%) [40], Southern Ethiopia (38.7%) [28], Mekelle (30.8%) [39], Gojjam (19.6%) [27], and Iran (29.6%) [44]. Interestingly, the prevalence of raised triglycerides (50.3%) in this study was higher than the results from Cameroon (18.9%) [58], Nigeria (9.9%] [59], Ethiopia (21.0%) [56], Malawi (28.7%) [60], Venezuela (39.7%) [61], Jordan (41.9%) [55], and Uganda (42.1%) [52]. This report, however, was lower than the result in Southern Ethiopia (62.2%) [28] but in line with findings reported in Thailand (49.9%) [51], India (56.1%) [49], South Africa (59.3%) [41], and Brazil (65.3%) [62]. Different study populations, methodology, ethnicity, lifestyle, length of hypertension, experiences with antihypertensive medications, and socioeconomic position could all contribute to variations in dyslipidemia prevalence.
Moreover, study discovered that the TC/HDL-C ratio is a strong marker for coronary heart disease. The risk of CVD has been heavily associated with a high TC/HDL-C ratio [63]. Thus, the current investigation found that a higher TC/HDL-c ratio was present in more than half (52.3%) of the study subjects. A study conducted in Karnataka revealed almost similar result (50.0%) [64], while Southern Ethiopia reported a lower result (36.1%) [28]. The difference may be caused by the varying research participant number, the presence of certain illnesses, the amount of dietary consumed, and the utilized cut-off values.
Significant relationships between dyslipidemia and the participant’s older age, gender, higher BMI, raised waist circumference, lack of fruit and vegetable consumption, sedentary lifestyle, comorbidity, long-term hypertension for more than five years, non-adherence to antihypertensive medications, and current smoking were also found. Dyslipidemia was seen in between 55.0 and 64.0% of people below the age of 40. This is higher than a previous Ethiopian study that revealed 18.7 to 32.5% [27] but lower than research results reported in other publications [65–71]. This increased frequency may be explained by the fact that middle-aged and older people were more vulnerable to the effects of many chronic diseases as physical function declined with age.
Additionally, this study found a positive correlation between elevated waist circumference and dyslipidemia, which is similar with the results of other earlier investigations [72–77]. Derangements in lipid profiles were present in 66.7 to 78.0%. Besides, respondents who were not engaged in regular physical activities experienced serum lipid abnormalities ranging from 52.1% to 66.9%. Similar findings were found in an earlier Ethiopian study that found lipid abnormalities in people who lead sedentary lifestyles to range from 26.4 to 64.4% [28]. Additionally, the prevalence of lipid change among obese, hypertensive people ranged from 76.5% to 91.2%, which is higher than the 32.3% to 56.9% seen in a previous Ethiopian study [27]. Dyslipidemia can develop in people who have sedentary lives, have high BMIs, and have large waist circumferences. Individuals with, sedentary lifestyles, raised BMI, and waist circumference might accumulate excessive fat, which leads to dyslipidemia. Besides, the variation among studies might be due to differences in the study population, methodology, age composition.
The results of the current investigation showed that sex and dyslipidemia were significantly linked. In line with this study, a number of earlier investigations found that the prevalence of dyslipidemia was much greater in women [27, 28, 78, 79]. On the other hand, a prior study found that men had a higher risk of dyslipidemia [80]. Additionally, respondents who had long-term hypertension (66.0 to 76.7%), a family history of hypercholesterolemia (69.2 to 84.6%), and diabetes co-morbidity (60.5 to 72.4%) showed atherogenic dyslipidemia. Dyslipidemia was also strongly linked to non-adherence to antihypertensive medications (55.5 to 73.5%) and infrequent consumption of fruits and vegetables (53.3 to 71.4%). A prior study in Harar, Ethiopia, revealed comparable results regarding consumption of fewer fruits and vegetables [40]. The prevalence of dyslipidemia was substantially correlated with current cigarette smoking, though, with a range of 43.3 to 71.7%, which is consistent with the results of other studies conducted in Saudi Arabia [71].
There were several restrictions placed on the study. The capacity to address causal links between dyslipidemia and its recognized risk variables among hypertension patients is constrained by all cross-sectional study methods, to start with. Second, since the information was gathered by a questionnaire, there could be a bias toward memory.
Conclusion
It can be concluded from this study that hypertensive patients frequently have atherogenic dyslipidemia, particularly low HDL-c and high triglyceride levels. Besides, the study indicated that age, gender, residence, BMI, the habit of eating fruits/vegetables, current smoking, regular physical activity, duration of hypertension, adhering to antihypertensive medicines, family history of hypercholesterolemia, and comorbidity were predictors of dyslipidemia. Therefore, it is crucial to perform suitable intervention programs aiming at risk factor reduction and establish regular screening programs for blood lipid concentrations in order to combat atherogenic dyslipidemia and the potential development of CVD. We suggest health education programs on behavioral and lifestyle changes for improving the health of hypertension patients based on the findings.
Acknowledgments
The authors would like to thank all study participants, data collectors, and all health institutions for their support.
References
- 1.
WHO W. A global brief on hypertension: silent killer, global public health crisis. 2013. https://scholar.google.com/scholar?cites=14631147074897551111&as_sdt=2005&sciodt=0,5&hl=en
- 2. Bosu WK, Reilly ST, Aheto JMK, Zucchelli E. Hypertension in older adults in Africa: A systematic review and meta-analysis. PLOSEONE. 2019; 14(4):1–25. pmid:30951534
- 3. Al‐Motarreb A, Baker K, Broadley KJ. Khat: pharmacological and medical aspects and its social use in Yemen. Phytotherapy Research: An International Journal Devoted to Pharmacological and Toxicological Evaluation of Natural Product Derivatives. 2002; 16(5):403–13. pmid:12203257
- 4. Ali WM, Al Habib KF, Al-Motarreb A, Singh R, Hersi A, Al Faleh H, et al. Acute coronary syndrome and khat herbal amphetamine use: An observational report. Circulation. 2011; 124(24):2681–9. pmid:22155995
- 5. Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton PK, He J. Global burden of hypertension: analysis of worldwide data. Lancet. 2005; 365(9455):217–23. pmid:15652604
- 6. Kibret KT, Mesfin YM. Prevalence of hypertension in Ethiopia: a systematic meta-analysis. Public Health Reviews. 2015; 36(1):1–2. pmid:29450042
- 7. Marchi-Alves LM, Rigotti AR, Nogueira MS, Cesarino CB, Godoy SD. Metabolic syndrome components in arterial hypertension. Revista da Escola de Enfermagem da USP. 2012; 46:1348–53.
- 8. Wabe NT. Chemistry, pharmacology, and toxicology of khat (catha edulis forsk): a review. Addiction & health. 2011; 3(3–4):137. pmid:24494129
- 9. Schmieder RE, Ruilope LM. Blood pressure control in patients with comorbidities. The Journal of Clinical Hypertension. 2008; 10(8):624–31. pmid:18772645
- 10. Mora S, Glynn RJ, Ridker PM. HDL particle concentration may better predict CVD event risk than HDL-c. Circulation. 2013; 128(11):1189–97.
- 11. Jacobson TA, Ito MK, Maki KC, Orringer CE, Bays HE, Jones PH, et al. National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1–executive summary. Journal of clinical lipidology. 2014; 8(5):473–88. pmid:25234560
- 12. Hanefeld M, Hora C, Schulze J, Rothe G, Barthel U, Haller H. Reduced incidence of cardiovascular complications and mortality in hyperlipoproteinemia (HLP) with effective lipid correction: The Dresden HLP Study. Atherosclerosis. 1984; 53(1):47–58. pmid:6497944
- 13. Brunzell JD, Davidson M, Furberg CD, Goldberg RB, Howard BV, Stein JH, et al. Lipoprotein management in patients with cardiometabolic risk: consensus conference report from the American Diabetes Association and the American College of Cardiology Foundation. Journal of the American College of Cardiology. 2008; 51(15):1512–24. pmid:18402913
- 14. Wilson PW, Anderson KM, Castelli WP, Kannel WB. Twelve-year incidence of coronary heart disease in middle-aged adults during the era of hypertensive therapy: the Framingham offspring study. The American journal of medicine. 1991; 90(1):11–6. pmid:1986576
- 15. DeFronzo RA, Ferrannini E. Insulin resistance: a multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes care. 1991; 14(3):173–94. pmid:2044434
- 16. Oparil S, Zaman MA, Calhoun DA. Pathogenesis of hypertension. Annals of internal medicine. 2003; 139(9):761–76. pmid:14597461
- 17.
World Health Organization. Global status report on alcohol and health 2018. World Health Organization; 2019.
- 18. Mansur AD, Favarato D. Trends in mortality rate from cardiovascular disease in Brazil, 1980–2012. Arquivos Brasileiros de Cardiologia. 2016 May 24;107:20–5. pmid:27223642
- 19. Castelli WP, Garrisson WP, Wilson PW, Abbott RD, Kalousdian S, Kannel WB. Incidence of coronary heart disease and lipid cholesterol levels: The Framingham study. JAMA. 1986; 256:2835–2838.
- 20. Cooney MT, Dudina A, De Bacquer D, Wilhelmsen L, Sans S, Menotti A, et al. HDL cholesterol protects against cardiovascular disease in both genders, at all ages and at all levels of risk. Atherosclerosis. 2009; 206(2):611–6. pmid:19375079
- 21. Smith S, Lall AM. A Study on lipid profile levels of diabetics and non-diabetics among Naini region of Allahabad, India. Turkish J Biochem. 2008; 33(4):138–141.
- 22. Cholesterol Education Program (NCEP). The third report of the National cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III) final report. Circulation 2002; 106:3143–421.
- 23.
World Health Organization. The atlas of heart disease and stroke / Judith Mackay and George Mensah; with Shanthi Mendis and Kurt Greenland. Geneva: World Health Organization 2004
- 24. Natarajan P, Ray KK, Cannon CP. High-density lipoprotein and coronary heart disease: current and future therapies. Journal of the American College of Cardiology. 2010; 55(13):1283–99. pmid:20338488
- 25. Nesto RW. Beyond low-density lipoprotein. American Journal of Cardiovascular Drugs. 2005; 5(6):379–87.
- 26. Noubiap JJ, Bigna JJ, Nansseu JR, Nyaga UF, Balti EV, Echouffo-Tcheugui JB, et al. Prevalence of dyslipidaemia among adults in Africa: a systematic review and meta-analysis. The Lancet Global Health. 2018; 6(9):e998–1007. pmid:30103999
- 27. Kifle ZD, Alehegn AA, Adugna M, Bayleyegn B. Prevalence and predictors of dyslipidemia among hypertensive patients in Lumame Primary Hospital, Amhara, Ethiopia: A cross-sectional study. Metabolism Open. 2021; 11:100108. pmid:34355158
- 28. Agete TH, Eshetu NG. Factors associated with atherogenic dyslipidemia among hypertensive patients at southern Ethiopia. International Journal of Medicine and Medical Sciences. 2018; 10(7):86–93.
- 29. Eaton CB. Hyperlipidemia. Primary Care: Clinics in Office Practice. 2005; 32(4):1027–55. pmid:16326226
- 30. Reddy KS. Cardiovascular disease in non-Western countries. New England Journal of Medicine. 2004; 350(24):2438–40. pmid:15190135
- 31. Dalal JJ, Padmanabhan T, Jain P, et al. Lipitension: interplay between dyslipidemia and hypertension. Indian J Endocrinol Metab 2012; 16: 240–245. pmid:22470861
- 32. Tilahun M, Gedefie A, Ebrahim E, Seid A, Ali A, Shibabaw A, et al. Immuno-Haematological Abnormalities of HIV-Infected Patients Before and After Initiation of Highly Active Antiretroviral Therapy in the Antiretroviral Therapy Clinics of Six Health Facilities at Dessie Town, Northeast Ethiopia. Journal of Blood Medicine. 2022; 13:243. pmid:35592587
- 33.
G. Douglas, F. Nicol, and C. Robertson, Eds., Macleod’s Clinical Examination E-Book, UK, 13th edition, 2013.
- 34. Alberti KGMM, Zimmet P, Shaw J. Metabolic syndrome—a new world-wide definition. A Consensus Statement from the International Diabetes Federation. 2006;469–80.
- 35. Rinkūnienė E, Laucevičius A, Petrulionienė Ž, Dženkevičiūtė V, Kutkienė S, Skujaitė A, et al. The prevalence of dislipidemia and its relation to other risk factors: a nationwide survey of Lithuania. Clinical Lipidology. 2015; 10(3):219–25.
- 36. Dave JA, Levitt NS, Ross IL, Lacerda M, Maartens G, Blom D. Anti-retroviral therapy increases the prevalence of dyslipidemia in South African HIV-infected patients. PloS one. 2016; 11(3):e0151911. pmid:26986065
- 37. Pajak A, Szafraniec K, Polak M, Polakowska M, Kozela M, Piotrowski W, et al. Changes in the prevalence, treatment, and control of hypercholesterolemia and other dyslipidemias over 10 years in Poland: the WOBASZ study. POLSKIE ARCHIWUM MEDYCYNY WEWNETRZNEJ-POLISH ARCHIVES OF INTERNAL MEDICINE. 2016; 126(9):642–52. pmid:27452484
- 38. Purwanto DS, Mewo YM, Jim EL. Evaluation of Lipid Profile on Hypertensive Patients: An Observational Study from North Sulawesi, Indonesia. Chest.2022; 6(1):39–44.
- 39. Gebreegziabiher G, Belachew T, Mehari K, Tamiru D. Prevalence of dyslipidemia and associated risk factors among adult residents of Mekelle City, Northern Ethiopia. PloS one. 2021; 16(2):e0243103. pmid:33561153
- 40. Sufa B, Abebe G, Cheneke W. Dyslipidemia and associated factors among women using hormonal contraceptives in Harar town, Eastern Ethiopia. BMC research notes. 2019; 12(1):1–7. pmid:30832721
- 41. Reiger S, Jardim TV, Abrahams-Gessel S, Crowther NJ, Wade A, Gomez-Olive FX, et al. Awareness, treatment, and control of dyslipidemia in rural South Africa: The HAALSI (Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa) study. PloS one. 2017; 12(10):e0187347. pmid:29077762
- 42. Bakesiima R, Byakika-Kibwika P, Tumwine JK, Kalyango JN, Nabaasa G, Najjingo I, et al. Dyslipidaemias in women using hormonal contraceptives: a cross sectional study in Mulago Hospital Family Planning Clinic, Kampala, Uganda. BMJ open. 2018; 8(10):e022338. pmid:30341126
- 43. Ali I, Kharma A, Samara M, Odeh S, Jaradat N, Zaid AN, et al. Prevalence of dyslipidemia in undiagnosed Palestinian men: a cross-sectional study. Journal of lipids. 2019; 2019. pmid:31737369
- 44. Najafipour H, Banivaheb G, Sabahi A, Naderi N, Nasirian M, Mirzazadeh A. Prevalence of anxiety and depression symptoms and their relationship with other coronary artery disease risk factors: A population-based study on 5900 residents in Southeast Iran. Asian Journal of Psychiatry. 2016; 20:55–60. pmid:27025473
- 45. Al-Nozha MM, Arafah MR, Al-Maatouq MA, Khalil MZ, Khan NB, Al-Marzouki K, et al. Hyperlipidemia in saudi arabia. Saudi medical journal. 2008; 29(2):282. pmid:18246242
- 46. Ogbeide DO, Karim A, Al-Khalifa IM, Siddique S. Population based study of serum lipid levels in Al-Kharj Health Center, Saudi Arabia. Saudi medical journal. 2004; 25(12):1855–7. pmid:15711654
- 47. Al-Shehri SN, Saleh ZA, Salama MM, Hassan YM. Prevalence of hyperlipidemia among Saudi school children in Riyadh. Annals of Saudi medicine. 2004; 24(1):6–8. pmid:15310005
- 48. Abalkhail BA, Shawky S, Ghabrah TM, Milaat WA. Hypercholesterolemia and 5-year risk of development of coronary heart disease among university and school workers in Jeddah, Saudi Arabia. Preventive medicine. 2000; 31(4):390–5. pmid:11006064
- 49. Banerjee R, Bhattacherjee S, Ray K, Roy JK, Datta S, Banerjee I. Dyslipidemia and its Relationship with Cardiovascular Risk Factors in a Selected Population of Siliguri City, West Bengal, India. Asian Journal of Medical Sciences. 2014; 5(1):1–8.
- 50. Azizi F, Rahmani M, Ghanbarian A, Emami H, Salehi P, Mirmiran P, et al. Serum lipid levels in an Iranian adults population: Tehran Lipid and Glucose Study. European journal of epidemiology. 2003; 18(4):311–9. pmid:12803371
- 51. Narindrarangkura P, Bosl W, Rangsin R, Hatthachote P. Prevalence of dyslipidemia associated with complications in diabetic patients: a nationwide study in Thailand. Lipids in health and disease. 2019; 18(1):1–8. pmid:30954084
- 52. Lumu W, Kampiire L, Akabwai GP, Ssekitoleko R, Kiggundu DS, Kibirige D. Dyslipidaemia in a Black African diabetic population: burden, pattern and predictors. BMC research notes. 2017; 10(1):1–7. pmid:29121994
- 53. Micah FB, Nkum BC. Lipid disorders in hospital attendants in Kumasi, Ghana. Ghana Medical Journal. 2012; 46(1). pmid:22605884
- 54. Doupa D, Mbengue AS, Diallo FA, Jobe M, Ndiaye A, Kane A, et al. Lipid profile frequency and the prevalence of dyslipidaemia from biochemical tests at Saint Louis University Hospital in Senegal. Pan African Medical Journal. 2014; 17(1). pmid:25018825
- 55. Abujbara M, Batieha A, Khader Y, Jaddou H, El-Khateeb M, Ajlouni K. The prevalence of dyslipidemia among Jordanians. Journal of lipids. 2018; 2018. pmid:30510803
- 56. Gebreyes YF, Goshu DY, Geletew TK, Argefa TG, Zemedu TG, Lemu KA, et al. Prevalence of high bloodpressure, hyperglycemia, dyslipidemia, metabolic syndrome and their determinants in Ethiopia: Evidences from the National NCDs STEPS Survey, 2015. PloS one. 2018; 13(5):e0194819. pmid:29742131
- 57. Obsa MS, Ataro G, Awoke N, Jemal B, Tilahun T, Ayalew N, et al. Determinants of Dyslipidemia in Africa: A Systematic Review and Meta-Analysis. Frontiers in cardiovascular medicine. 2021; 8. pmid:35284497
- 58. Ama Moor VJ, Ndongo Amougou S, Ombotto S, Ntone F, Wouamba DE, Ngo Nonga B. Dyslipidemia in patients with a cardiovascular risk and disease at the University Teaching Hospital of Yaoundé, Cameroon. International journal of vascular medicine. 2017; 2017. pmid:28163932
- 59. Anyabolu EN. Dyslipidemia in people living with HIV-AIDS in a tertiary hospital in South-East Nigeria. Pan African Medical Journal. 2017; 28(1). pmid:29610642
- 60. Amberbir A, Singano V, Matengeni A, Ismail Z, Kawalazira G, Chan AK, et al. Dyslipidemia among rural and urban HIV patients in south-east Malawi. PLoS One. 2018; 13(5):e0197728. pmid:29782548
- 61. González-Rivas JP, Nieto-Martínez R, Brajkovich I, Ugel E, Rísquez A. Prevalence of dyslipidemias in three regions in Venezuela: the VEMSOLS study results. Arquivos Brasileiros de Cardiologia. 2018; 110:30–5. pmid:29538522
- 62. Feitosa AC, Barreto LT, Silva IM, Silva FF, Feitosa GS. Impact of the use of different diagnostic criteria in the prevalence of dyslipidemia in pregnant women. Arquivos Brasileiros de Cardiologia. 2017; 109:30–8. pmid:28591252
- 63. Zhai F, He Y, Hu Y, Wang Z, Yu W, Yang X. The status of dietary fiber intake of Chinese people in 2002. Acta Nutrimenta Sinica. 2005; 27:444–7.
- 64. Pramiladevi R, Gooranavar SM, Biradar SB, Baragundi MC, Kora SA, Narayan M. Study of lipid profile in Hypertensive patients in rural Karnataka. Journal of Pharmaceutical and Biomedical Sciences. 2011; 7(18):1–6.
- 65. Das H, Banik S. Prevalence of dyslipidemia among the diabetic patients in southern Bangladesh: A cross-sectional study. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2019; 13(1):252–7. pmid:30641707
- 66. Pan J, Ren Z, Li W, Wei Z, Rao H, Ren H, et al. Prevalence of hyperlipidemia in Shanxi Province, China and application of Bayesian networks to analyse its related factors. Scientific reports. 2018; 8(1):1–9. pmid:29491353
- 67. Wang Y, Aung LH, Tan JY, Yin RX, Hu XJ, Long XJ, et al. Prevalence of dyslipidemia and its risk factors in the Chinese Maonan and Han populations. Int J Clin Exp Pathol. 2016; 9(10):10603–16.
- 68. Qi L, Ding X, Tang W, Li Q, Mao D, Wang Y. Prevalence and risk factors associated with dyslipidemia in Chongqing, China. International journal of environmental research and public health. 2015; 12(10):13455–65. pmid:26516874
- 69. Gallon CW, Mendes KG, Theodoro H, Vargas JG, Miecinikovsski R, De Lorenzi DR, et al. SUN-P120: Dyslipidemia among Climacteric Women in Southern Brazil. Clinical Nutrition. 2017; 36:S98–9.
- 70. Wang S, Xu L, Jonas JB, You QS, Wang YX, Yang H. Prevalence and associated factors of dyslipidemia in the adult Chinese population. PloS one. 2011; 6(3):e17326. pmid:21423741
- 71. Al-Kaabba AF, Al-Hamdan NA, El Tahir A, Abdalla AM, Saeed AA, Hamza MA. Prevalence and correlates of dyslipidemia among adults in Saudi Arabia: results from a national survey. 2012; 2(4):24553–9
- 72. Opoku S, Gan Y, Fu W, Chen D, Addo-Yobo E, Trofimovitch D, et al. Prevalence and risk factors for dyslipidemia among adults in rural and urban China: findings from the China National Stroke Screening and prevention project (CNSSPP). BMC public health. 2019; 19(1):1–5. pmid:31711454
- 73. Garcez MR, Pereira JL, Fontanelli MD, Marchioni DM, Fisberg RM. Prevalence of dyslipidemia according to the nutritional status in a representative sample of São Paulo. Arquivos brasileiros de cardiologia. 2014; 103:476–84. pmid:25590927
- 74. Darroudi S, Saberi‐Karimian M, Tayefi M, Arekhi S, Motamedzadeh Torghabeh A, Seyedzadeh Sani SM, et al. Prevalence of combined and noncombined dyslipidemia in an Iranian population. Journal of Clinical Laboratory Analysis. 2018; 32(8):e22579. pmid:29926995
- 75. Al-Duais MA, Al-Awthan YS. Association between qat chewing and dyslipidaemia among young males. Journal of Taibah University Medical Sciences. 2019; 14(6):538–46. pmid:31908642
- 76. Zaid M, Ameer F, Munir R, Rashid R, Farooq N, Hasnain S, et al. Anthropometric and metabolic indices in assessment of type and severity of dyslipidemia. Journal of physiological anthropology. 2017; 36(1):1–0. pmid:28241855
- 77. Biadgo B, Abebe SM, Baynes HW, Yesuf M, Alemu A, Abebe M. Correlation between serum lipid profile with anthropometric and clinical variables in patients with type 2 diabetes mellitus. Ethiopian journal of health sciences. 2017; 27(3):215–26. pmid:29217920
- 78. Bekele S, Yohannes T, Mohammed AE. Dyslipidemia and associated factors among diabetic patients attending Durame General Hospital in Southern Nations, Nationalities, and People’s Region. Diabetes, metabolic syndrome and obesity: targets and therapy. 2017; 10:265. pmid:28790859
- 79. Henock A, Techalew S, Kinfe L. Dyslipidemia among diabetic patients in Southern Ethiopia: cross-sectional study. Journal of Diabetes and Endocrinology. 2015; 6(4):19–24.
- 80. Madssen E, Laugsand LE, Wiseth R, Mørkedal B, Platou C, Vatten L, et al. Risk of acute myocardial infarction: dyslipidemia more detrimental for men than women. Epidemiology. 2013; 24(5):637–42. pmid:23873070