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. 2022 Jul 21;11:20480040221114651. doi: 10.1177/20480040221114651

Dyslipidemia and associated cardiovascular risk factors in HIV-positive and HIV-negative patients visiting ambulatory clinics: A hospital-based study

Minyahil A Woldu 1,2,✉, Omary Minzi 1, Ephrem Engidawork 2
PMCID: PMC9309774  PMID: 35898404

Abstract

Background

Dyslipidemia is a well-known risk factor for cardiovascular disease (CVD), accounting for more than half of all instances of coronary artery disease globally (CAD).

Purpose

The purpose of this study was to determine lipid-related cardiovascular risks in HIV-positive and HIV-negative individuals by evaluating lipid profiles, ratios, and other related parameters.

Methods

A hospital-based study was carried out from January 2019 to February 2021 in both HIV + and HIV- ambulatory patients.

Results

High TG (p = .003), high TC (p = .025), and low HDL (p < .001) were all associated with a two-fold increased risk of CVD in people aged 45 and up. Due to higher TG (p < .001) and lower HDL (p < .001), males were found to have a higher risk of atherogenic dyslipidemia. A twofold increase in the likelihood of higher TG levels has been associated with smoking (p = .032) and alcohol intake (p = .022). A twofold increase in a high TC/HDL ratio and an elevated TG/HDL ratio was observed with an increase in waist-to-height ratio (p = .030) and a high level of FBS (126 mg/dl) and/or validated diabetes (p = .017), respectively. In HIV + participants, central obesity (p < .001), diabetes (p < .001), and high blood pressure (p < .001) were all less common than in HIV- participants.

Conclusions

Dyslipidemia is linked to advanced age, male gender, diabetes, smoking, alcohol consumption, and increased waist circumference, all of which could lead to an increased risk of CVD, according to the study. The study also revealed that the risks are less common in HIV + people than in HIV-negative ambulatory patients.

Keywords: Dyslipidemia, Cardiovascular risks, Ambulatory patients

Introduction

Dyslipidemia is a well-known risk factor for cardiovascular disease (CVD), accounting for more than half of all instances of coronary artery disease (CAD) globally. 1 The mechanism of atherosclerosis that leads to CVD is difficult to diagnose before the appearance of serious clinical outcomes such as CVD-related death, myocardial infarction (MI), or stroke. 2 Several studies have found a wide number of CVD risk variables, which can be split into non-modifiable risk factors like age and gender and modifiable risk factors including smoking, blood pressure (BP), and diabetes mellitus (DM). 3 Because low-density lipoprotein cholesterol (LDL-C) is the principal cholesterol-carrying lipoprotein and is believed to be the main atherogenic lipoprotein, 4 its levels are optimized in primary and secondary prevention measures to minimize cardiovascular risks. 5 Other lipoproteins, such as high-density lipoprotein cholesterol (HDL-C) or very-low-density lipoprotein (VLDL), have also been found to have a role in atherogenesis on multiple occasions.6–8

Excessive weight gain, such as for overweight & obesity, has emerged as a major global health concern, 9 increasing the risk of DM and CVD.10,11 Despite this link, there are obese patients without metabolic abnormalities known as “metabolically healthy obese” (MHO), as well as normal-weight patients with metabolic abnormalities known as “metabolically unhealthy normal weight” (MUH-NW).12–15 Individuals of normal weight who are at an increased risk of metabolic illnesses such as type 2 diabetes (T2DM) are classified as MUH-NW. MHO is usually diagnosed based on normal glucose and lipid metabolism indicators, as well as the absence of hypertension (HTN), whereas MUH-NW are individuals of normal weight who are at an elevated risk of metabolic illnesses such as DM and HTN.16,17

Waist circumference (WC) and waist-to-height ratio (WHtR), in addition to BMI, can be utilized as surrogate biomarkers of body fat centralization and cardiovascular risks. 18 Finding risk variables to target to avoid or minimize mortality risk has thus become vital, even in people of normal weight.15,19,20 However, there are no universally accepted standards for establishing whether or not someone is metabolically healthy. 20

In clinical investigations, hyperinsulinemia or insulin resistance (IR) and carotid intima-media thickness (CIMT) are widely utilized biomarkers for predicting lipid-associated cardiovascular risk.21,22 Nonalcoholic fatty liver disease (NAFLD) is also connected to IR, hyperglycemia, and T2DM.23,24 To predict and diagnose a wide range of lipid-related risks, a variety of biomarkers, both specific and non-specific, can be utilized and are available.25,26 For many patients, reliable measurement of several techniques in clinical practice is difficult or impossible due to a variety of factors. 27 The use of simple rapid tests to establish lipid profiles is gaining popularity due to its cost-effectiveness and time-saving capabilities.15,28,29 Even if disparities in discriminating power among populations, as well as variations in rapid test cut-off points, remained an issue. 15

HIV-positive people are known to have an increased risk of cardiovascular disease (CVD) for a variety of reasons, including pathophysiology and the use of antiretroviral therapy (ART). However, this risk, which is prevalent in people living with HIV/AIDS (PLWHA), must be compared to other people with chronic conditions and who are not using ART drugs. As a result, the goal of this study was to determine lipid-related cardiovascular risks in HIV-positive compared to HIV-negative individuals by evaluating lipid profile patterns, ratios, and other related parameters.

Methods

Study design, period, and setting

Patients visiting the HIV and adult ambulatory clinics of Zewditu Memorial Hospital (ZMH), Addis Ababa, Ethiopia, were studied in a hospital-based observational study from January 25, 2019, to February 25, 2021. This institution has been at the forefront of establishing and launching ART therapy services in Ethiopia since 2003. 30 In addition to HIV counseling and testing, sexually transmitted infection services, and post-exposure prophylaxis treatments, it offers various clinical services and palliative care to the general public. As a general hospital, it provides a wide range of services through its clinics, departments, and wards. Every month, ZMH serves approximately 1163 HIV-positive patients and over 3000 HIV-negative patients.

Study population

The source population consisted of patients who came to ZMH for treatment of HIV and other chronic illnesses. Patients who met the study's inclusion criteria made up the study's population.

Inclusion and exclusion criteria

Inclusion criteria

The study included all patients who were 18 years or older, had at least three appointments completed, and were willing to participate.

Exclusion criteria

During the cohort period, severely unwell patients, and pregnant and breastfeeding women were excluded. Patients with HIV who went to ambulatory clinics for reasons other than ART were also excluded so as to avoid double entry.

Sample size determination and sampling technique

The following sample size estimation of independent cohort studies was used to calculate the sample size for the study population. 31

n=[Z1−α/2(1+1/m)p*(1−p)+Z1−βp0*(1−p0/m)p1(1−p1)]2(p0−p1)2

The sample size was calculated using a two-sided significance criterion (1-alpha) of 95%, a power (1-beta, percent probability of detecting) of 80%, a ratio of Unexposed/Exposed = 1, and a percentage of Exposed with Outcome of 11.3%. 32 A sample size of (n = 620) determined with 10% contingency for (n = 320) HIV-positive and the rest (n = 300) HIV-negative group. The baseline sample size was complete for (n = 510) participants comprising 288 HIV + and 222 HIV-negative patients. To enroll study participants, a systematic random sampling technique was adopted.

Data collection

Laboratory testing, clinical examinations and measurements, patient interviews, and chart reviews were used to gather detailed information about the participants. The structured questionnaire employed by the WHO stepwise method for non-communicable disease risk factor surveillance was adapted for a face-to-face interview (STEPS-2014). 33 The questionnaire asks about age, religion, civil status, address, educational level, occupation, monthly income, substance use (tobacco, alcohol, coffee, Khat plant use), and use of any prescription and non-prescription medications. Height and weight (body mass index/ BMI), waist circumferences (WC), blood pressure (BP), fasting blood sugar (FBS), and lipid profile were determined through a physical examination and laboratory tests.

Study procedure

All participants in this study were classified as HIV + if they were registered at an ART clinic for follow-up treatment, and HIV-negative if they were registered at an adult ambulatory clinic for follow-up care and tested negative for HIV within the last 6 months.

Borderline, high, and very high cholesterol values were frequently used to mark severity and classify treatment options considering bad cholesterol. 34 Low and very low were terms that were used to describe good cholesterol, and high-density lipoprotein (HDL).35,36

Dyslipidemia 37 is defined when one or more of the following are present in both males and females aged 19 and up. 1. Total cholesterol (TC) > 240 mg/dl; 2. non-high-density lipoprotein (non-HDL-C) > 130; 3. Low density lipoprotein (LDL) > 160 mg/dl; 4. TG > 201 mg/dL in both males (M) and females (F) aged 19 and up, and 5. When HDL-C <40 mg/dL (M) or <50 mg/dL (F).

The following Cholesterol Ratios to Predict CVD were employed. 38 1. Waist circumference: Overweight: >94 cm (M); >80 cm (F); Obesity: >102 cm (M); >88 cm (F). 2. Waist to height ratio: Overweight: 0.53 to 0.89 (M) & 0.49 to 0.84 (F); Obesity: ≥0.90 cm (M); ≥0.85 cm (F). 3. TC/HDL-C ratio: Ideal: Less than 3.5 (M) < 3.0 (F); Moderate: 3.5 to 5.0 (M) 3.0 to 4.4 (F); High: More than 5.0 (M) > 4.4 (F). 4. LDL-C/HDL-C ratio: Ideal, less than 2.5; Moderate, 2.5 to 3.3; High, more than 3.3. 5. HDL/LDL ratio: Ideal, more than 0.4; Moderate, 0.4 to 0.3; High, less than 0.3. 6. TG/HDL ratio: Ideal: Less than 3.5 (M) < 3.0 (F); Moderate: 3.5 to 5.0 (M) 3.0 to 4.4 (F); High: More than 5.0 (M) > 4.4 (F).

Instruments

Omron HEM 7203 was used to measure BP (Omron Healthcare Co. Ltd, Kyoto, Japan). The devices were calibrated regularly to ensure correct validation. The accuracy of the devices was also tested using a Mercury sphygmomanometer. Before taking measurements, an appropriate BP arm cuff in suitable sizes was applied. Before BP measures, participants were allowed to sit and relax for 5 min without talking, with their legs uncrossed and their arms supported at heart level. The mean of three BP readings taken from the right arm with a 5-min interval was used for analysis.38,39 SIEMENS (Dimension EXL 200 Integrated Chemistry System), Omnia Health (CS-T240 Auto-Chemistry Analyzer), and LipidPlus® were used to examine lipid profiles and glucose levels.

Data analysis

IBM statistics software version 25 for Windows was used to code, double-enter, and analyze the data. All categorical characteristics were categorized as 0 or 2 (for females with no responses and HIV-negative) or 1 (for males with yes responses and HIV + ). The dependent variables were coded as dichotomous measurements (low-risk was coded as ‘0 or 2’ and ‘Moderate to high-risk’ was coded as ‘1’).

To present sociodemographic data, incidence, and prevalence data, descriptive statistics were used. The connections of predictors with the outcome variables were determined using logistic regression analysis. To control the effect of confounders, independent variables with a p-value of 0.20 in the bivariate logistic regression were incorporated into multivariate logistic regression. Statistical significance was defined as a 95% confidence interval and a p-value of less than 0.05.

Results

General characteristics of study participants

When compared to participants younger than 45 years old, those aged 45 and more were twice as likely to have high TG (p = .003), high TC (p = .025), and low HDL (p < .001). Males were 2 times as likely as females to have high TG (p < .001) and 6 times as likely to have low HDL-C (p < .001).

Smokers (p = .032) and alcoholics (p = .022) had twice the amount of high TG as non-smokers and non-alcoholics, respectively. Those who consumed alcohol, on the other hand, were less likely to have high TC (p = .044) than those who were not. Other factors like civil status, family history, and HIV status had no significant impact on the specific dyslipidemias. Details are shown in Table 1.

Table 1.

The socio-demographic characteristics of participants based on triglycerides, total cholesterol, and high-density lipoprotein cholesterol distribution at the zewditu memorial hospital in Addis Ababa, Ethiopia, 2021.

Characteristics Triglycerides (mg/dl) OR (95%CI) P. value Total cholesterol (mg/dl) OR (95%CI) P. value HDL-C (mg/dl) OR (95%CI) P. value
≥ 201 n (%) <201 ≥ 240 n (%) Else n (%) <40 (M) or <50 (F) n (%) Else n (%)
Age ≥45 103 (81.7) 259 (67.4) 2.161 (1.311, 3.563) .003 63 (81.8) 299 (69.1) 2.017 (1.092, 3.726) .025 158 (81.4) 204 (64.6) 2.410 (1.569, 3.701) <.001
<45 23 (18.3) 125 (32.6) 14 (18.2) 134 (30.9) 36 (18.6) 112 (35.4)
Gender Male 70 (55.6) 143 (37.2) 2.107 (1.401, 3.167) <.001 32 (41.6) 181 (41.8) .990 (.605, 1.619) .968 135 (69.6) 78 (24.7) 6.982 (4.686, 10.402) <.001
Female 56 (44.4) 241 (62.8) 45 (58.4) 252 (58.2) 59 (30.4) 238 (75.3)
Civil status Married 64 (50.8) 191 (49.7) 1.043 (.697, 1.560) .873 37 (48.1) 218 (50.3) .912 (.562, 1.482) .711 106 (54.6) 149 (47.2) 1.350 (.943, 1.933) .101
Elsea 62 (49.2) 193 (50.3) 40 (51.9) 215 (49.7) 88 (45.4) 167 (52.8)
Edu. status College & above 48 (38.1) 128 (33.3) 1.231 (.811, 1.868) .330 31 (40.3) 145 (33.5) 1.339 (.814, 2.201) .520 77 (39.7) 99 (31.3) 1.443 (.993, 2.095) .054
Elseb 78 (61.9) 256 (66.7) 46 (59.7) 288 (66.5) 117 (60.3) 217 (68.7)
Address Kirkos 49 (39.2) 141 (37.0) 1.097 (.725, 1.662) .661 31 (40.8) 159 (37.0) 1.174 (.714, 1.931) .527 79 (41.1) 111 (35.4) 1.279 (.884, 1.849) .192
Elsec 76 (60.8) 240 (63.0) 45 (59.2) 271 (63.0) 113 (58.9) 203 (64.6)
Income ≥50USD 68 (54.0) 204 (53.1) 1.034 (.691, 1.549) .869 40 (51.9) 232 (53.6) .937 (.576, 1.522) .791 107 (55.2) 165 (52.2) 1.126 (.786, 1.611) .518
<50USD 58 (46.0) 180 (46.9) 37 (48.1) 201 (46.4) 87 (44.8) 151 (47.8)
FH Yes 29 (23.0) 81 (21.1) 1.115 (.688, 1.805) .659 18 (23.4) 92 (21.3) 1.127 (.634, 2.005) .683 42 (21.6) 68 (21.6) 1.004 (.650, 1.550) .987
No 97 (77.0) 302 (78.9) 59 (76.6) 340 (78.7) 152 (78.4) 247 (78.4)
TM Yes 17 (13.5) 37 (9.7) 1.458 (.790, 2.693) .285 12 (15.6) 42 (9.7) 1.714 (.857, 3.429) .128 19 (9.8) 35 (11.1) .869 (.482, 1.566) .639
No 109 (86.5) 346 (90.3) 65 (84.4) 390 (90.3) 175 (90.2) 280 (88.9)
Smoker Yes 15 (11.9) 23 (6.0) 2.115 (1.067, 4.193) .032 3 (3.9) 35 (8.1) .460 (.138, 1.534) .206 20 (10.3) 18 (5.7) 1.903 (.980, 3.695) .057
No 111 (88.1) 361 (94.0) 74 (96.1) 397 (91.9) 174 (89.7) 298 (94.3)
Alcohol Yes 28 (22.2) 52 (13.6) 1.819 (1.090, 3.034) .022 6 (7.8) 74 (17.1) .409 (.171,.976) .044 38 (19.6) 42 (13.3) 1.583 (.979, 2.561) .061
No 98 (77.8) 331 (86.4) 71 (92.2) 358 (82.9) 156 (80.4) 273 (86.7)
Coffee consumption Yes 85 (67.5) 240 (62.7) 1.235 (.807, 1.892) .331 48 (62.3) 277 (64.1) .926 (.561, 1.529) .764 125 (64.4) 200 (63.5) 1.042 (.717, 1.512) .830
No 41 (32.5) 143 (37.3) 29 (37.7) 155 (35.9) 69 (35.6) 115 (36.5)
Khat chewing Yes 8 (6.3) 20 (5.2) 1.231 (.528, 2.867) .631 3 (3.9) 25 (5.8) .660 (.194, 2.242) .505 11 (5.7) 17 (5.4) 1.054 (.483, 2.300) .896
No 118 (93.7) 363 (94.8) 74 (96.1) 407 (94.2) 183 (94.3) 298 (94.6)
HIV-status HIV +  69 (54.8) 219 (57.0) .912 (.608, 1.367) .656 41 (53.2) 247 (57.0) .858 (.527, 1.395) .536 107 (55.2) 181 (57.3) .917(.640, 1.315) .639
HIV- 57 (45.2) 165 (43.0) 36 (46.8) 186 (43.0) 87 (44.8) 135 (42.7)
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n = 510 (288 (HIV + ), 222 (HIV-)); a: includes Widowed/er, divorced, and never married; b: includes illiterate, primary, secondary, and high schoolers; c: includes Gulelle, Arada, Kolfe, Addis Ketema, Nefas Silk Lafto, Lidetea, Yeka, Bole, and Akaki Kality; OR: is according to Mantel-Haenszel OR estimate (95%CI). FH, family history of cardiometabolic diseases.

When it came to the TC/HDL-C ratio, the male gender was less likely to be associated with a moderate to a high level of TC/HDL ratio (p < .001), whereas WHtR (p = .030), and high FBS and/or confirmed DM (p = .017) were two-fold more likely to be associated with an elevated TC/HDL ratio after correcting for the confounders. Other variables such as MUH-NW and MHO showed no significant association with TC/HDL-C ratio (Table 2).

Table 2.

Total cholesterol to high-density lipoprotein cholesterol ratio among participants at the zewditu memorial hospital in Addis Ababa, Ethiopia, 2021.

Description TC/HDL ratio COR (95% CI) P. value AOR (95% CI) P value
Moderate to high Normal
Age ≥45 years
>/ = 40 264 (73.7) 98 (64.5) 1.548 (1.030, 2.325) .036 1.345 (.842, 2.148) .215
<45 94 (26.3) 54 (35.5)
Gender (M)
Male 131 (36.6) 82 (53.9) .493 (.335,.724) <.001 .468 (.304,.720) .001
Female 227 (63.4) 70 (46.1)
Civil status
Married 171 (47.8) 84 (55.3) .740 (.506, 1.084) .122 .690 (.459, 1.037) .074
Else 187 (52.2) 68 (44.7)
Edu
College & above 120 (33.5) 56 (36.8) .864 (.582, 1.284) .471
Else 238 |(66.5) 96 (63.2)
Monthly income
>/ = 50 USD 193 (53.9) 79c (52.0) 1.081 (.739, 1.581) .688
<50 USD 165 (46.1) 73 (48.0)
Family history
Yes 81 (22.7) 29 (19.1) 1.963 (1.256, 2.000) .366
No 235 (65.6) 120 (78.9)
Central Obesity
WC >35′ (F) 0r ≤ 40’ (M) 125 (34.9) 22 (14.5) 3.170 (1.920, 5.234) <.001 1.478 (.803, 2.723) .210
WC ≤ 35′ (F) 0r >40′ (M) 233 (65.1) 130 (85.5)
BMI
Over-weight & Obesity 113 (31.6) 27 (17.8) 2.135 (1.332, 3.423) .002 1.283 (.764, 2.154) .346
Normal-BMI 245 (68.4) 125 (82.2) 1
High FBS or Confirmed DM
FBS ≥ 126 mg/dl or DM 113 (31.6) 27 (17.8) 2.135 (1.332, 3.423) .002 1.739 (1.052, 2.875) .031
FBS < 126 mg/dl or No DM 245 (68.4) 125 (82.2)
SBP >120 & DBP>80 or HTN
Pre-HTN and HTN 214 (59.9) 71 (46.7) 1.707 (1.165, 2.503) .006 1.473 (.960, 2.261) .076
Normal BP 143 (40.1) 81 (53.3)
MUH_NW
Yes 224 (62.6) 100 (65.8) .869 (.584, 1.294) .490
Else 134 (37.4) 52 (34.2)
MHO
Yes 87 (24.3) 30 (19.7) 1.306 (.819, 2.082) .263
Else 271 (75.7) 122 (80.3)
WHtR
>.50 248 (69.3) 74 (48.7) 2.376 (1.610, 3.508) <.001 1.676 (1.052, 2.669) .030
Else 110 (30.7) 78 (51.3)
HIV status
HIV +  202 (70.1) 86 (29.9) .994 (.678, 1.457) .974
HIV- 156 (70.3) 66 (29.7)
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Moderate to high, >/ = 3. 5 (M) & >/ = 3.0 (F); Normal, <3.5 (M) & <3.0 (F) .

Before and after adjusting for confounders, none of the covariates were shown to have a significant link with increasing LDL/HDL-C ratio (Table 3).

Table 3.

Low-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio among study participants at the zewditu memorial hospital in Addis Ababa, Ethiopia, 2021.

Characteristics LDL/HDL ratio COR (95% CI) P value AOR (95% CI) P value
Moderate to high Normal
Age ≥45 years
>/ = 40 177 (74.4) 185 (68.0) 1.365 (.927, 2.009) .115 1.229 (.810, 1.864) .332
<45 61 (25.6) 87 (32.0)
Gender (M)
Male 98 (41.2) 115 (42.3) .956 (.672, 1.360) .801
Female 140 (58.8) 157 (57.7)
Civil status
Married 118 (49.6) 137 (50.4) .969 (.684, 1.372) .859
Else 120 (50.40 135 (49.6)
Address
Kirkos 94 (39.8) 96 (35.6) 1.200 (.837, 1.721) .322
Else 142 (60.2) 174 (64.4)
Educational status
College & above 36.6% 32.7% 1.185 (.822, 1.708) .364
Else 63.4% 67.3%
Monthly income
>/ = 50 USD 137 (57.6) 135 (49.6) 1.377 (.970, 1.954) .074 1.385 (.965, 1.987) .077
<50 USD 101 (42.4) 137 (50.4)
Family history
Yes 54 (22.8) 56 (20.6) 1.138 (.746,.1737) .548
No 183 (77.2) 216 (79.4)
Central Obesity
WC >35′ (F) 0r ≤ 40′ (M) 78 (32.8) 69 (25.4) 1.434 (.976, 2.107) .066 1.207 (.769, 1.894) .413
WC ≤ 35′ (F) 0r >40′ (M) 160 (67.2) 203 (74.6)
BMI
Over-weight & Obesity 76 (31.9) 79 (29.0) 1.146 (.785, 1.672) .479
Normal-BMI 162 (68.1) 193 (71.0)
High FBS or DM
FBS ≥126 or confirmed DM 31.9 (76) 64 (23.5) 1.525 (1.031, 2.254) .034 1.306 (.868, 1.963) .200
FBS <126 or confirmed DM 162 (68.1) 208 (76.5)
High BP or confirmed HTN
SBP>120 mmHg and DBP> 80mmHg 141 (59.5) 144 (52.9) 1.306 (.918, 1.856) .138 1.126 (.774, 1.638) .535
Else 96 (40.5) 128 (47.1)
MUH_NM
BMI <125 Kg/m2 but with DM/HTN 149 (62.6) 175 (64.3) .928 (.647, 1.332) .685
Else 89 (37.4) 97 (35.7)
MHO
BMI ≥125 Kg/m2 but without DM/HTN 51 (21.4) 66 (24.3) .851 (.562, 1.290) .448
Else 187 (78.6) 206 (75.7)
WHtR
>.50 161 (67.6) 161 (59.2) 1.442 (1.002, 2.074) .049 1.221 (.801, 1.860) .354
Else 77 (32.4) 111 (40.8)
HIV-status
HIV +  137 (47.6) 151 (52.4) 1.087 (.765, 1.544) .642
HIV- 101 945.5) 121 (54.5)
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Moderate to high, ≥ 2.5; Central obesity is according to the NCEP definition (waist circumference >35 inches in Women and >40 inches in men).

Age, central obesity, BMI, DM, HTN, and WHtR were all found to be linked with higher TG/HDL-C ratios, but after controlling for variables, only DM (hyperglycemia) was shown to be substantially associated with high TG/HDL-C ratio (AOR = 1.597, 95 percent CI (1.061, 2.404; p = .025). Details are shown in Table 4.

Table 4.

Triglyceride to high-density lipoprotein cholesterol ratio among study participants at the zewditu memorial hospital in Addis Ababa, Ethiopia, 2021.

Characteristics TG/HDL ratio COR (95% CI) P value AOR (95% CI) P value
Moderate to high Normal
Age ≥45 years
>/ = 40 165 (76.7) 197 (66.8) 1.642 (1.102, 2.445) .015 1.284 (.839, 1.965) .249
<45 50 (23.3) 98 (33.2)
Gender (M)
Male 96 (44.7) 117 (39.7) 1.227 (.860, 1.752) .259
Female 119 (55.3) 178 (60.3)
Civil status
Married 113 (52.6) 142 (48.1) 1.194 (.840, 1.697) .324
Else 102 (47.4) 153 9 (51.9)
Address
Kirkos 83 (39.2) 107 (36.4) 1.124 (.781, 1.618) .528
Else 129 (60.8) 187 (63.6)
Educational status
College & above 70 (32.6) 106 (35.9) .861 (.594, 1.248) .429
Else 145 (67.4) 189 (64.1)
Monthly income
>/ = 50 USD 119 (55.3) 153 (51.9) 1.150 (.808, 1.637) .436
<50 USD 96 (44.7) 142 (48.1)
Family history
Yes 51 (23.7) 59 (20.1) 1.239 (.810, 1.894) .323
No 164 (76.3) 235 (79.9)
Central Obesity
WC >35′ (F) 0r ≤ 40′ (M) 75 (34.9) 72 (24.4) 1.659 (1.128, 2.442) .010 1.204 (.726, 1.996) .473
WC ≤ 35′ (F) 0r > 40′ (M) 140 (65.1) 223 (75.6)
BMI
Over-weight & Obesity 75 (34.9) 80 (27.1) 1.440 (.984, 2.106) .060 1.077 (.696, 1.667) .740
Normal-BMI 140 (65.1) 215 (72.9)
High FBS or DM
FBS ≥126 or confirmed DM 74 (34.4) 66 (22.4) 1.821 (1.230, 2.697) .003 1.597 (1.061, 2.404 .025
FBS <126 or confirmed DM 141 (65.6) 229 (77.6)
High BP or confirmed HTN
SBP>120 mmHg and DBP> 80mmHg 136 (63.3) 149 (50.7) 1.675 (1.170, 2.400) .005 1.422 (.967, 2.092) .073
Else 79 (36.7) 145 (49.3)
MUH_NM
BMI <125 Kg/m2 but with DM/HTN 140 (65.1) 184 (62.4) 1.126 (.781, 1.624) .525
Else 75 (34.9) 111 (37.6)
MHO
BMI ≥125 Kg/m2 but without DM/HTN 52 (24.2) 65 (22.0) 1.129 (.745, 1.712) .568
Else 163 (75.8) 230 (78.0)
WHtR
>.50 152 (70.7) 170 (57.6) 1.774 (1.221, 2.578) .003 2.975 (.317, 27.967) .340
Else 63 (29.3) 125 (42.4)
HIV status
HIV +  123 (42.7) 165 (57.3) .994 (.678, 1.457) .974
HIV- 92 9(41.4) 130 (58.6)
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Central obesity (AOR = .316, 95 percent CI (.186,.538), p < .001), diabetes (AOR = .330, 95 percent CI (.203,.535), p < .001), and high blood pressure (AOR = .339 (.227,.507), p < .001) were all less common in HIV + participants than in HIV- participants. WHtR (AOR = 2.973 (1.831, 4.828), p < .001) was the only type of dyslipidemia factor that was substantially linked with HIV + subjects.

Discussion

Only a few studies have been found in the scholarly literature that compares HIV-negative ambulatory patients with chronic illnesses to HIV-positive patients.40,41 Dyslipidemia has been linked to a higher risk of CVD in ambulatory diabetic patients,42,43 and it is also seen often in HIV-positive patients on protease inhibitors. 44 In clinical settings, assessing and quantifying risk in these populations through comparative research could be highly useful for optimal drug therapy management. The purpose of this study was to use data from ambulatory individuals’ lipid profiles to predict the risk of CVD.

Table 1 shows that people aged 45 and up had a two-fold increased risk of CVD in the form of elevated TG (AOR = 2.161, 95% CI (1.311, 3.563), p = .003), elevated TC (AOR = 2.017, 95% CI (1.092, 3.726), p = .025), and a decline in HDL (AOR = 2.410, 95% CI (1.569, 3.701), regardless of the HIV status. Several studies have found a link between age and dyslipidemia, albeit the specific cut-off age differs depending on the scientific literature.45,46 According to one study, the prevalence of dyslipidemia rises in tandem with the progression of diabetes mellitus as people get older. 47 As liver and kidney function deteriorates with age, it is also possible that this will affect lipid metabolism, leading to dyslipidemia.48,49

Males were found to have a greater risk of dyslipidemia due to higher TG (AOR = 2.107, 95% CI (1.401, 3.167), p < .001), and lower HDL (AOR = 6.982, 95% CI (4.686, 10,402), p < .001). A high TG and low HDL describe atherogenic dyslipidemia and insulin resistance, which is also a risk factor for CAD and stroke.50,51 Atherogenic dyslipidemia was more common in men than in women, which could be because most men smoke and are genetically predisposed to lipid-related CVD. This finding was supported by several other investigations.52,53

As stated above concerning gender, smoking has been linked to a higher TG level (p = .032), with smokers being two times more likely than non-smokers. 54 The likely explanation is that smoking impairs the function of lipoprotein lipase and hormone-sensitive lipase, both of which are regulated by insulin and catecholamines, causing dysregulation and an increase in TG levels. 55 This finding was consistent with prior research that linked cigarette smoking to an increased risk of atherosclerosis, 56 and also several other studies.57–59

Alcohol consumption was also linked to higher TG levels, with the odds being doubled in alcoholics compared to non-alcoholics (p = .022). Epidemiologic data generally demonstrate an inverse relationship between CAD risk and moderate alcohol consumption, which is characterized in various ways but roughly equates to 1 to 2 pints of beer per day. 60 The influence of fasting TG level arising from the effect of alcohol in liver cells can be explained in connection with the involvement of underlying genetic disorders of TG metabolism in increasing TG with alcohol consumption.60,61 This finding is in agreement with several other studies.58,59,62

Lipoprotein ratios can provide information on risk variables that are difficult to measure using traditional methods, and they may be a better reflection of metabolic and clinical interactions between lipid fractions.63,64 Because lipoprotein ratios are underutilized in cardiovascular prevention but can help with risk assessment, 65 we used the three most frequent types of ratios to predict the risks in this investigation as shown in table 2.

An increase in WHtR resulted in a twofold rise in a high-Tc/HDL ratio (AOR = 1.676, 95% CI (1.052, 2.669), p = .030). Because the population's height remains constant over time, the only element that influences this could become the WC. According to the findings, utilizing WHtR as an indicator of ‘early health risk’ is easier and more accurate than using a matrix based on BMI or waist circumference alone. 66 Hence, the measurement could be used to track the risk of CAD and NAFLD.

A high level of FBS (≥ 126 mg/dl) and/or verified DM (p = .017) were also connected to a two-fold greater risk of having an elevated TC/HDL ratio. The association between a high WHtR and DM is best explained by the fact that these individuals are prone to metabolic disturbances that can lead to central obesity. This is well addressed in various scientific findings.66,67 Individuals who have increased WHtR could also be prone to develop, CAD, NAFLD, or stroke.68–72 This ratio determination has also been shown to be a better predictor of CIMT advancement than HDL-C or LDL-C alone in a prospective investigation.73,74

Table 4 shows the other lipoprotein ratio, TG/HDL-C, and only DM (hyperglycemia) was shown to be significantly linked with it (AOR = 1.597, 95% CI (1.061, 2.404; p = .025), indicating metabolic dysregulation in this population and its contribution to dyslipidemia once again. The TG/HDL-C ratio can be used to detect IR, cardiometabolic risk, and CVD (9, 10). As a result, a widely available and standardized measurement of the TG/HDL-C ratio is expected to aid clinicians in identifying individuals who are not just IR but also have dyslipidemia. 15 A high TG/HDL-C ratio has also been revealed to be a strong predictor of major adverse cardiac events (MACE) such as cardiac death, nonfatal MI, or reintervention, as well as an independent predictor of long-term all-cause mortality. 75 Several studies have also used the TG/HDL-C ratio to determine childhood obesity-related CVD.76,77

As shown in table 5, dyslipidemias and related factors were compared based on HIV status, and variables like central obesity (AOR = .316, 95% CI (.186,.538), p < .001), diabetes (AOR = .330, 95% CI (.203,.535), p < .001), and high blood pressure (AOR = .339 (.227,.507), p < .001) were all less common in the HIV + participants than in the HIV-negatives. The most plausible explanation is that two-thirds of HIV-negative participants had diabetes mellitus (DM), and the rest had other conditions that contributed to the disparities. Diabetes mellitus, as previously noted, is the leading cause of dyslipidemia and CVD in persons aged 45 and up.78,79

Table 5.

Dyslipidemia based on HIV status of the participants at the zewditu memorial hospital in Addis Ababa, Ethiopia, 2021.

HIV-positive HIV-negative COR (95% CI) P value AOR (95% CI) P value
BMI
Over-weight and obesity (≥ 25 kg/m2) 92 (31.9) 63 (28.4) 1.185 (.808, 1.737) .386
Normal (<25 kg/m2) 196 (68.1) 159 (71.6)
Obesity (NCEP)
WC >35 inch in Women and >40 inch in men 68 (23.6) 79 (35.6) .559 (.380,.824) .003 .316 (.186,.538) <.001
WC </ = 35 inch in Women and </ = 40 inch in men 220 (76.4) 143 (64.4)
High FBS or DM
FBS ≥126 or confirmed DM 50 (17.4) 90 (40.5) .308 (.205,.462) <.001 .330 (.203,.535) <.001
Else (<126) 238 (82.6) 132 (59.5)
High BP or confirmed HTN
SBP>120 mmHg and DBP> 80mmHg 129 (44.9) 156 (70.3) .345 (.345,.500) <.001 .339 (.227,.507) <.001
Else 158 (55.1) 66 (29.7)
MUH_NM
BMI <125 Kg/m2 but with DM/HTN 168 (58.3) 156 (70.3) .592 (.409,.858) .006 .583 (.317, 1.074) .084
Else 120 (41.7) 66 (29.7)
MHO
BMI ≥125 Kg/m2 but without DM/HTN 80 (27.8) 37 (16.7) 1.923 (1.242, 2.977) .003 1.206 (.563, 2.582) .630
Else 208 (72.2) 185 (83.3)
High TC
≥240 mg/dl 41 (14.2) 36 (16.2) .536 (.527, 1.395) .858
< 240 mg/dl 247 (85.8) 186 (83.8)
High Non-HDL-C
≥130 mg/dl 163 (56.6) 131 (59.0) .906 (.635, 1.292) .585
<130 mg/dl 125 (43.4) 91 (41.0)
High LDL-C
≥160 mg/dl 42 (14.6) 31 (14.0) 1.052 (.637, 1.736) .843
<160 mg/dl 246 (85.4) 191 (86.0)
LDL/HDL ratio
>/ = 2.5 moderate to high 137 (47.6) 101 (45.5) 1.087 (.765, 1.544) .642
<2.5 normal 151 (52.4) 121 (54.5)
TC/HDL ratio
>/ = 3. 5 (M) & >/ = 3.0 (F) Moderate to high 202 (70.1) 156 (70.3) .994 (.678, 1.457) .974
<3.5 (M) & <3.0 (F) Normal 86 (29.9) 66 (29.7)
TG/HDL ratio
>/ = 3. 5 (M) & >/ = 3.0 (F) Moderate to high 123 (42.7) 92 (41.4) 1.053 (.739, 1.502) .774
<3.5 (M) & <3.0 (F) Normal 165 (57.3) 130 (58.6)
WHtR
>.50 193 (67.0) 199 (58.1) 1.465 (1.019, 2.105) .039 2.973 (1.831, 4.828) <.001
Else 95 (33.0) 93 (41.9)
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Limitation of the study

Because the data was only obtained from a single hospital, the study cannot be considered a representative of all HIV + and HIV− ambulatory patients. Again, since clinical events or surrogate evidence such as coronary plaque was not determined using computed CT, the lipid-related CVD risk calculated in this study may not represent a genuine CVD. During the follow-up phase, good application of preventive clinical guidelines and a healthy lifestyle modification can also help to reduce the risk of CVD.

Conclusion

Dyslipidemia is linked to advanced age, male gender, diabetes, smoking, alcohol consumption, and increased waist circumference, all of which could lead to an increased risk of CVD, according to the study. The study also revealed that the risks are less common in HIV + people than in HIV-negative ambulatory patients. Diabetes mellitus was the most common cause of dyslipidemia and cardiovascular disease in people aged 45 and up.

Operational definitions

Terms Interpretations
Alcohol-consumption defined as the use of any form of alcohol-based beverages whether locally produced or manufactured in industries, and used regularly in any interval ranging from days to month by the participant/s at present in any amount. Occasional intakes for holidays, ceremonies, a greater than monthly interval intakes were neglected.
Cigarette smoking defined as the active use of tobacco whether locally produced or manufactured in industries, and is being used regularly by the participant/s at present in any form or amount on a daily, weekly basis, or monthly intervals.
Coffee- consumption defined as the use of coffee whether locally produced or manufactured in industries, and is being used regularly by the participant/s at present in any amount on a daily or weekly basis.
Family history of cardiometabolic disease defined concerning the positive history of cardiovascular diseases (diabetes, hypertension, heart failure, coronary heart disease, or dyslipidemia) in a first-degree relative.
HIV- negative An individual on follow-up care of adult ambulatory clinics for other chronic diseases management such as diabetes, hypertension, etc., and have no HIV during enrollment.
HIV- positive An individual confirmed HIV + by either antigen or antibody tests and has already initiated combination ART (cART) by attending the ART follow-up service.
Khat-chewing defined as the regular use of Khat leaves by the participant/s at present in any form or amount on a daily, weekly basis, or monthly intervals.
MHO Defined as metabolically healthy obese patients 16 and they are overweight/ obesity patients (≥25 Kg/m2) but without dyslipidemia, T2DM, or HTN.
MUH-NW Defined as metabolically unhealthy normal weight 16 and participants within the normal BMI (<25 Kg/m2) but having a T2DM or FBS>126 mg/dl or HTN will be considered MUH-NW
Normal-weight Defined as BMI 18.5–24.9 kg/m2
Obesity defined as a BMI of ≥ 30 kg/m2
Overweight defined as a body mass index or BMI of 25 to 29.9 kg/m2
Traditional medicine defined as the use of any non-conventional medicine that was prescribed in any form of remedies to be administered to any part of the body and that is being used at present in any amount and any interval.
WHtR Defined as Waist to Height Ratio and if it is greater than 0.5 in adults are considered to be a risk for cardiometabolic disorders. 80
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Annexes

Annex 1.

Target cholesterol levels by age and sex 39

Age and sex Total cholesterol Non-HDL cholesterol LDL cholesterol
People aged 19 years and younger (children and teens) Borderline: 170-199 mg/dL
High: Greater than or equal to 200 mg/dL		 Borderline: 120-144 mg/dL
High: Greater than or equal to 145 mg/dL		 Borderline: 110-129 mg/dL
High: Greater than or equal to 130 mg/dL
Men aged 20 years
and older		 Borderline: 200-239 mg/dL
High: Greater than or equal to 239 mg/dL
​		 High: Greater than 130 mg/dL Near optimal or above optimal: 100-129 mg/dL
Borderline high: 130-159 mg/dL
High: 160-189 mg/dL
Very high: Greater than 189 mg/dL
Women aged 20 years
and older		 Borderline: 200-239 mg/dL
High: Greater than or equal to 239 mg/dL		 High: Greater than 130 mg/dL Near optimal or above optimal: 100-129 mg/dL
Borderline high: 130-159 mg/dL
High: 160-189 mg/dL
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Annex 2.

High total, non-HDL, and LDL cholesterol levels by age and sex39

Age and sex Total cholesterol Non-HDL cholesterol LDL cholesterol
People aged 19 years and younger (children and teens) Borderline: 170-199 mg/dL
High: Greater than or equal to 200 mg/dL		 Borderline: 120-144 mg/dL
High: Greater than or equal to 145 mg/dL		 Borderline: 110-129 mg/dL
High: Greater than or equal to 130 mg/dL
Men aged 20 years
and older		 Borderline: 200-239 mg/dL
High: Greater than or equal to 239 mg/dL
​		 High: Greater than 130 mg/dL Near optimal or above optimal: 100-129 mg/dL
Borderline high: 130-159 mg/dL
High: 160-189 mg/dL
Very high: Greater than 189 mg/dL
Women aged 20 years
and older		 Borderline: 200-239 mg/dL
High: Greater than or equal to 239 mg/dL		 High: Greater than 130 mg/dL Near optimal or above optimal: 100-129 mg/dL
Borderline high: 130-159 mg/dL
High: 160-189 mg/dL
Very high: Greater than 189 mg/dL
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Footnotes

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Deutscher Akademischer Austauschdienst,

ORCID iD: Minyahil A. Woldu https://orcid.org/0000-0002-3163-0326

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