Journal of Obesity
Volume 2021 (2021), Article ID 1578653, 10 pages
https://doi.org/10.1155/2021/1578653

Research Article

Central Obesity and Associated Factors among Adult Patients on Antiretroviral Therapy (ART) in Armed Force Comprehensive and Specialized Hospital, Addis Ababa, Ethiopia

Adnan Kemal,¹ Mohammed Ahmed,² Melese Sinaga Teshome,³ and Kalkidan Hassen Abate³

¹Department of Public Health, College of Health Science, Defense University, Addis Ababa, Ethiopia
²Department of Public Health, College of Health Science, Woldia University, Woldia, Ethiopia
³Department of Nutrition and Dietetics, Jimma University, Jimma, Ethiopia

Correspondence should be addressed to Adnan Kemal; adnankemale@gmail.com

Received 19 June 2020; Revised 9 October 2020; Accepted 12 August 2021; Published 31 August 2021

Academic Editor: Nunzio Velotti

Copyright © 2021 Adnan Kemal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Background. Similar to the general population, the prevalence of central obesity is increasing among HIV-infected persons. There are little data on the burden of abdominal obesity using the waist-to-hip ratio measurement in HIV-infected patients in resource-limited settings, including Ethiopia. Therefore, this study aimed to assess the prevalence and associated factors of central obesity among HIV patients taking ART in an armed force comprehensive and specialized hospital, Addis Ababa, Ethiopia. Methods. A cross-sectional study was conducted from March to April 2018. A systematic sampling method was used to select 353 study participants. Pretested World Health Organization stepwise questionnaire, document review, and anthropometric and biochemical measurements were used to collect data on different variables under the study. The collected data were entered into EpiData version 3 and analyzed by SPSS version 21. An adjusted odds ratio with 95% CI was considered to declare a statistically significant association. Results. The prevalence of central obesity in this study was 71.7% (95% CI: 67%–76.4%). Besides, the odds of central obesity were associated with being female (AOR: 85.6; 95% CI: 20.09, 364.6), among merchants (AOR: 18.8; 95% CI: 1.39, 255.7), CD4 count <200 cells/mm³ (AOR: 0.03; 95% CI: 0.007, 0.160), among respondents taking AZT + 3TC + EFV-based ART regimen (AOR: 8.73; 95% CI: 1.33, 57.17), ABC + 3TC + ATV/r-based regimen (AOR: 0.18; 95% CI: 0.03, 0.94), increased BMI (AOR: 3.50; 95% CI: 1.36, 3.89), and abnormal blood pressure (AOR: 2.53; 95%: 1.13, 5.67). Conclusion. It is possible to conclude that central obesity is a huge public health problem among the HIV-infected population in the study area. Being female, increased BMI, low CD4 count, AZT + 3TC + EFV, ABC + 3TC + ATV/r-based regimen, and abnormal blood pressure were associated with central obesity. Therefore, adequate attention must be paid to primary and secondary control of these factors to reduce the prevalence of abdominal obesity among HIV-infected patients.

1. Introduction

Effective viral suppression through the prolonged use of antiretroviral treatment (ART) has dramatically improved prognosis and survival evidenced by declining the toll of AIDS-related deaths [1]. In Ethiopia, an estimated 0.9% of men and women aged 15–49 years have been infected with the Human Immune Virus (HIV), and 71% of the eligible patients are currently on antiretroviral therapy (ART) [2].

People living with treated HIV infection today enjoy greater life expectancy and thus are more exposed to the obesogenic environment and accumulate age-related cardiometabolic risk factors [1, 3]. HIV-infected patients appear to frequently develop increased visceral fat and metabolic syndrome after starting ART regimen [4, 5].

Studies showed that obesity affects 2 in 5 HIV-infected women and 1 in 5 HIV-infected men compared with men and women in the general population, respectively [6]. HIV-infected patients had more abdominal visceral fat than extremity fat and demonstrated a higher waist-to-hip ratio (WHR) compared to the control population [7–9]. Similar to the general population, the prevalence of central obesity (the localized accumulation of adipose tissue in the abdomen irrespective of proportion to total body fat) is increasing among HIV-infected persons, for instance, 4% in the United States [10], 12.6% in Tanzania [11], 36.5% in Malaysia [12], and 45.7% in Brazil [13].

Different factors were implicated for central obesity such as female gender [14], advanced age (age of 40–49 years and ≥50 years) [10, 12, 14], higher CD4+ lymphocyte count (>350 cells/mm³) [10, 14], higher fasting plasma glucose [12], and higher body mass index (BMI) [12]. Evidence also showed that, for every increase of 10 g of lipid intake, the odds of central obesity increased 1.28 times. Carbohydrate consumption showed a negative association with central obesity [13].

Central obesity has been shown to correlate strongly with metabolic syndrome, hyperuricemia, and the progression of coronary calcium scores, which is a marker of cardiovascular disease (CVD) [15–18]. Also, abdominal adiposity is directly related to accelerating the aging process of the immune system [5], increased risk of dementia, fatty liver disease [5, 18], obstructive sleep apnea [19], reduced self-reported quality of life, decreased ART adherence, and a fear of disclosure of HIV status [20].

Currently, WHR is not so often used for evaluating central adiposity in the general population, and in its place waist circumference is the most widespread anthropometric measurement used. Besides, minimal agreement with BMI in identifying HIV/AIDS patients with increased cardiometabolic risk was reported [21]. Hence, WHR is useful in detecting possible signs of excess fat deposition in those infected with HIV [7, 13, 18].

Even though numerous studies have been conducted on central obesity concerning HIV infection and ART in developed countries, there are few data on the burden of abdominal obesity using WHR in HIV-infected patients in resource-limited settings, including Ethiopia in general, and no study was done in the study area in particular. Therefore, this study aimed to assess the prevalence and associated factors of central obesity among HIV-infected patients taking ART in an armed force comprehensive and specialized hospital, Addis Ababa, Ethiopia, for the first time.

2. Methods and Materials

2.1. Study Setting and Design

A cross-sectional study was conducted from March to April 2018 at an armed force comprehensive and specialized hospital, Addis Ababa, which is the capital city of Ethiopia, the seat of the African Union, and economic commission for Africa. The hospital has been delivering health services to the defense forces including civilians in the Ministry of Defense. The hospital launched a free ART program at the end of 2003. The total number of subjects ever enrolled for HIV care before the study period was 4,329 (4,053 adults and 276 children). From the total numbers of adult subjects ever enrolled for HIV care, 2,263 adults were currently on ART in the hospital; from this, 1750 subjects were followed up during the study period.

Individuals living with HIV/AIDS, aged ≥18 years, who had been receiving ART for at least 6 months or more and was able to communicate and provide informed consent were included in the study. Pregnant women and individuals who had a physical deformity of the waist and hip were excluded from the study.

2.2. Sample Size Determination and Sampling Procedure

The sample size was calculated by using a single population proportion formula by taking a 50% proportion of central obesity among HIV patients on ART, since there was no study conducted in Ethiopia using WHR, 95% CI, and 5% margin of error, and the minimum final sample size becomes 384. The systematic sampling method was employed to select the study participants every 5th interval after preparing a sampling frame based on patient order when coming to the hospital for follow-up.

2.3. Definition of Central Obesity

We used the European cutoff point to interpret the waist-to-hip circumference ratio measurement for sub-Saharan African people according to International Diabetes Federation (IDF) recommendations; central obesity was defined as waist-to-hip ratio (WHR) ≥0.94 cm for men and ≥0.80 cm for women [22, 23].

2.4. Data Collection Instrument and Procedure

2.4.1. Face-to-Face Interview

Data were collected using a structured questionnaire adapted from the WHO stepwise approach to chronic disease risk factor surveillance [24]. The questionnaire contained sociodemographic characteristics (age, sex, marital status, educational status, and occupation). Questions related to depression (by using the Beck Depression Inventory score) and individual dietary diversity score (DDS) were added to supplement the WHO STEPwise approach. WHO stage during ART initiation, duration on ART, baseline CD4 count, viral load count, and type of ART regimen were collected from the patient’s health record.

2.4.2. Anthropometric Measurements

Weight, height, waist circumference, and hip circumference were measured using calibrated equipment. Weight was measured using the SECA 704 medical weighing scale. Body mass index was calculated by dividing a person’s weight in kilograms by the square of their height in meters. Waist circumference was measured at the horizontal plane which corresponds to the midpoint between the anterior superior iliac spine and the lower costal margin at the midclavicular line. Also, hip circumference measurement was done for participants by using a SECA 200 cm measuring tape. To improve the reliability of measurement for all anthropometric measurements, two readings were taken and the average of the two readings was recorded as the final measurement of the respondent.

2.4.3. Blood Pressure Measurements

Blood pressure (BP) was measured using a standard adult arm cuff of mercury type sphygmomanometer after 5 min rest in the clinic by the nurses working in the ART clinic. To improve the reliability of measurement, three readings were taken with 5 min intervals and the average of the three readings was recorded as the final BP of the patient. But if the difference between the two readings was greater than 5 mmHg, a third measurement was taken and recorded as the final BP of the patient.

2.4.4. Biochemical Measurements

Fasting blood was collected and analyzed by qualified laboratory technologists for biochemical measurements. The study subjects were requested to return to the clinics to provide fasting blood samples (4 ml) for blood glucose, lipid profile (triglyceride, total cholesterol levels, HDL-c, and LDL-c), and current CD4 count measurements the next day in case if they had eaten and the test was done in next morning. All measurements were analyzed in the Cobas Mira Plus spectrophotometer (Roche Diagnostics) equipped with calibration filters and DIASYS serum control.

2.5. Data Collection Procedure

The questionnaire was first written in English and then translated into Amharic and back to English by linguistic experts, and it was tested before use. A research team of nine individuals (4 ART nurses, 1 public health expert, 2 laboratory technicians, and 2 lab technologists) collected data on sociodemographic characteristics and performed clinical, behavioral, anthropometric, blood pressure, and biochemical measurements. A supervisory team (1 public health expert and 1 lab technologist) including the principal investigator was in place during the data collection. Both the interviewers and supervisors were trained for two days on the objective of the study, methods on how to collect data and interviewing approach, anthropometric measurement, biochemical measurement, and blood pressure measurement.

2.6. Data Quality Assurance

The proper functioning of instruments, laboratory reagents, and technical performance was checked by using quality control samples (serum pool). Standard operating procedures (SOPs) were followed starting from sample collection up to result reporting. All laboratory procedures were handled by laboratory technologists. Before data analysis, cleaning was done.

2.7. Data Processing and Analysis

The data were collected, cleaned, and checked for completeness and consistency manually. They were coded and entered into EpiData version 3.1. Then they were exported to SPSS (version 21.0) for further cleaning and statistical analysis. Descriptive statistics such as frequency, percentage, mean, and standard deviation were used to describe characteristics of the study population. Bivariate analysis was done using binary logistic regression, a variable of interest, and all covariate variables which had an association with the outcome variables at a value of less than 0.25 were selected for multivariable binary logistic regression analysis. Multivariable binary logistic regression models were used to isolate independent predictors of central obesity. A two-sided value <0.05 along with an adjusted odds ratio (AOR) of 95% confidence interval was considered to declare statistically significant associations. The fitness of the model was checked using the Hosmer–Lemeshow test and the model was fitted having a value of 0.57.

2.8. Ethical Consideration

Ethical clearance was obtained from the Institutional Review Board of the Institute of Health, Jimma University, and then permission was obtained from the armed force comprehensive and specialized hospital review board and ART clinic head. Written informed consent was secured from each study subject after the benefit, risk, and danger of participation were explained. Confidentiality was assured and maintained. A thumbprint or signature was used on the consent form. If the participants were diagnosed with lipid abnormality, fasting glucose impairment, and increased blood pressure, he/she was linked to the hospital for chronic care proper treatment, and follow-up of this disease as well coincides with HIV/ART disease. Every laboratory investigation was done according to the requirement of the patient. Health education on risk factors, consequences, and complications were provided to all of the participants after the compilation of data collection.

3. Results

3.1. Descriptive Statistics of the Study Participants

A total of 353 respondents were included and analyzed in this study, yielding a response rate of 97%. 172 (48.7%) respondents were female. The mean age of the participants was 44.6 ± 8.85 years. Regarding education, 205 (58.1%) respondents have attended primary/secondary education. Concerning occupation, 87 (24.6%) of them were employed. Looking upon marital status, 248 (70.3%) respondents were married (Table 1).

Table 1: Sociodemographic profile of the HIV patients who received ART at armed force comprehensive and specialized hospital, Ethiopia, 2018 (n = 353).

Variables
Category
Frequency (%)

Sex
Female
172 (48.7)

Male
181 (51.3)

Age (mean ± SD)
Mean: 44.6 ± 8.85 years

Educational status
Illiterate
50 (14.2)

Primary/secondary
205 (58.1)

College and above
98 (27.8)

Occupation
Housewife
50 (14.2)

Employer
87 (24.6)

Merchant
52 (14.7)

Pensioners
19 (5.4)

Unemployed
145 (41.1)

Marital status
Married
248 (70.3)

Never married
31 (8.8)

Widowed
34 (9.6)

Divorced
40 (11.3)

3.2. Clinical and Behavioral Characteristics of Study Participants

117 (33.1%) respondents were found to be at WHO clinical stage II at baseline. After ART initiation, 209 (59.2%) of them had >107 months of ART duration at the time of the survey. Moreover, 185 (52.4%) respondents were found in TDF + 3TC + EFV-based ART regimen. The proportions of the participants who smoked cigarettes, drank alcohol, and chewed khat were 13 (3.7%), 131 (37.1%), and 12 (3.4%), respectively. 288 (81.6%) respondents were depressed at the time of the survey (Table 2).

Table 2: Clinical and behavioral characteristics of HIV patients who received ART at armed force comprehensive and specialized hospital, Ethiopia, 2018 (n = 353).

Variables
Category
Frequency (%)

WHO clinical stage
Stage I
57 (16.1)

Stage II
117 (33.1)

Stage III
109 (30.9)

Stage IV
70 (19.8)

Duration on ART
<59 months
48 (13.6)

60–107 months
96 (27.2)

>107 months
209 (59.2)

Type of regimen
AZT + 3TC + NPV
68 (19.3)

AZT + 3TC + EFV
30 (8.5)

TDF + 3TC + EFV
185 (52.4)

TDF + 3TC + NPV
37 (10.5)

ABC + 3TC + ATZ
12 (3.4)

ABC + 3TC + ATV/r
21 (5.9)

Smoked cigarette
Yes
13 (3.7)

No
340 (96.3)

Consumed alcohol
Yes
131 (37.1)

No
222 (62.9)

Physical activity
Yes
244 (69.1)

No
109 (30.9)

Chewed khat
Yes
12 (3.4)

No
341 (96.6)

Dietary diversity score (DDS)
Diversified
195 (55.2)

Undiversified
158 (44.8)

Depression status
Yes
288 (81.6)

No
65 (18.4)

3.3. Laboratory and Anthropometry-Related Parameters among the Study Participants

The mean levels of TC, LDL, and HDL were 1.99.3 (±46.3), 117.6 (±56.4), and 49.1 (±14.82) mg/dl, respectively. The mean baseline and current CD4 counts were 182.58 (±144.19) and 455.69 (±262.84), respectively. The mean recent viral load was 10895.9 ± 79634. Likewise, the mean of the FBS level of the study participants was 108.55 (±48.879) mg/dl. As well, the mean waist circumference and hip circumference of the participants were 88.8 (±9.97) and 94.68 (±9.28) cm respectively (Table 3).

Table 3: Laboratory and anthropometry-related parameters among HIV patients who received ART at armed force comprehensive and specialized hospital, Ethiopia, 2018 (n = 353).

Parameters
Mean ± SD

Total cholesterol (TC)
199.3 (±46.3) mg/dl

Low-density lipoprotein (LDL)
117.6 (±56.4) mg/dl

High-density lipoprotein(HDL)
49.1 (±14.82) mg/dl

Total triglycerides (TG)
137.6 (±78.9) mg/dl

Fasting blood glucose (FBS)
108.5 (±48.9) mg/dl

Waist circumference
88.8 (±9.97) cm

Hip circumference
94.68 (±9.28) cm

Body mass index
23.17 (±4.094) kg/m²

Baseline CD4 counts
182.58 (±144.19) cells per mm³

Current CD4 counts
455.69 (±262.84) cells per mm³

Recent viral load
10895.9 ± 79634 copies per ml

3.4. Prevalence of Central Obesity among HIV Patients Who Received ART at Armed Force Comprehensive and Specialized Hospital

The prevalence of central obesity in this study was 71.7% (95% CI: 67%–76.4%). 155 (43.9%) female respondents developed central obesity. Besides, 138 (39.1%) respondents who developed central obesity attended primary/secondary education. As well, 94 (26.6%) respondents who developed central obesity were found to be at WHO clinical stage II at baseline. Furthermore, 154 (43.6%) respondents who developed central obesity had >107 months of ART duration. 125 (35.4%) respondents who developed central obesity were found in TDF + 3TC + EFV-based ART regimen. Among the participants who developed central obesity, 92 (26.1%) consumed alcohol. 129 (36.5%) of the respondents had abnormal total cholesterol (TC), and 172 (48.7%) had abnormal low-density lipoprotein (LDL) (Table 4).

Table 4: Prevalence of central obesity among HIV patients who received ART at armed force comprehensive and specialized hospital, Ethiopia, 2018 (n = 353).

Variables
Category
WHR

Abnormal (%)
Normal (%)

Sex
Female
155 (43.9)
17 (4.8)

Male
98 (27.8)
83 (23.5)

Educational status
Illiterate
42 (11.9)
8 (2.3)

Primary/secondary
138 (39.1)
67 (19.1)

College and above
73 (20.7)
25 (7.1)

Occupational status
Housewife
45 (12.7)
5 (1.4)

Employed
111 (31.4)
39 (11.0)

Merchant
17 (4.8)
2 (0.6)

Pensioners
60 (17.0)
50 (14.2)

Unemployed
20 (5.7)
4 (1.1)

Marital status
Married
177 (50.1)
71 (20.1)

Never married
20 (5.7)
11 (3.1)

Widowed
30 (8.5)
4 (1.1)

Divorced
26 (7.4)
14 (4.0)

WHO clinical stage
Stage I
34 (9.6)
23 (6.5)

Stage II
94 (26.6)
23 (6.5)

Stage III
79 (22.4)
30 (8.5)

Stage IV
46 (13.0)
24 (6.8)

Duration on ART (months)
<59 months
34 (9.6)
14 (4.0)

60–107 months
65 (18.4)
31 (8.8)

>107 months
154 (43.6)
55 (15.6)

Type of regimen
AZT + 3TC + NPV
54 (15.3)
14 (4.0)

AZT + 3TC + EFV
28 (7.9)
2 (0.6)

TDF + 3TC + EFV
125 (35.4)
60 (17.0)

TDF + 3TC + NPV
29 (8.2)
8 (2.3)

ABC + 3TC + ATZ
5 (1.4)
7 (2.0)

ABC + 3TC + ATV/r
12 (3.4)
9 (2.5)

Baseline CD4 counts (cells/mm³)
<200
173 (49.0)
60 (17.0)

200–349
47 (13.3)
29 (8.2)

350–499
20 (5.7)
10 (2.8)

>500
13 (3.7)
1 (0.3)

Current CD4 counts (cells/mm³)
<200
17 (4.8)
16 (4.5)

200–349
38 (10.8)
23 (6.5)

350–499
61 (17.3)
17 (4.80)

>500
137 (38.8)
44 (12.5)

Current viral load
≤1000 counts
234 (66.3)
86 (24.4)

≥1001 counts
19 (5.4)
14 (4.0)

Smoked cigarette
Yes
9 (2.5)
4 (1.1)

No
244 (69.1)
96 (27.2)

Consumed alcohol
Yes
92 (26.1)
39 (11.0)

No
161 (45.6)
61 (17.3)

Physical activity
Yes
176 (49.9)
68 (19.3)

No
77 (21.8)
32 (9.1)

Dietary/diversity score
Diversified
139 (39.4)
56 (15.9)

Undiversified
114 (32.3)
44 (12.5)

Depression status
Normal
206 (58.4)
82 (23.2)

Abnormal
47 (13.3)
18 (5.1)

Total cholesterol (TC)
Normal
129 (36.5)
62 (17.6)

Abnormal
124 (35.1)
38 (10.80)

Low-density lipoprotein (LDL)
Normal
172 (48.7)
71 (20.1)

Abnormal
81 (22.9)
29 (8.2)

High-density lipoprotein (HDL)
Normal
155 (43.9)
72 (20.4)

Abnormal
98 (27.8)
28 (7.9)

Total triglyceride (TG)
Normal
175 (49.6)
76 (21.5)

Abnormal
78 (22.1)
24 (6.8)

Blood pressure (BP)
Normal
149 (42.2)
69 (19.5)

Abnormal
104 (29.5)
31 (8.8)

3.5. Factors Associated with Central Obesity among HIV Patients Who Received ART at Armed Force Comprehensive and Specialized Hospital, Ethiopia

All the variables were entered into multivariate binary logistic regression analysis by the enter method of model selection. After adjusting for potential confounders by logistic regression, sex, occupational status, type of ART regimen, current CD4 counts, BMI, and abnormal blood pressure were associated with central obesity.

In this study, the odds of central obesity were 85.6 (AOR: 85.6; 95% CI: 20.09, 364.6) times higher among females compared to males. Likewise, the odds of central obesity were 18.8 (AOR: 18.8; 95% CI: 1.39, 255.7) times higher among merchants compared to housewives.

Moreover, the odds of central obesity were decreased by 97% (AOR: 0.03; 95% CI: 0.007, 0.160) among participants who had a CD4 count <200 cells/mm³ compared to respondents who had a CD4 count >500 cells/mm³.

Likewise, the odds of central obesity were 8.73 (AOR: 8.73; 95% CI: 1.33, 57.17) times higher among respondents taking AZT + 3TC + EFV compared to AZT + 3TC + NPV-based ART regimen. However, participants taking ABC + 3TC + ATV/r-based regimen were 82% (AOR: 0.18; 95% CI: 0.03, 0.94) protective against central obesity compared to AZT + 3TC + NPV-based ART regimen.

As the BMI of the participants increased by 1 kg/m², the odds of central obesity increased by 3.5 (AOR: 3.50; 95% CI: 1.36, 3.89).

The odds of central obesity were 2.53 (AOR: 2.53; 95%: 1.13, 5.67) times higher among participants who had abnormal blood pressure when compared to their counterparts (Tables 5 and 6).

Table 5: A bivariate analysis using binary logistic regression to identify factors associated with central obesity among HIV patients who received ART at armed force comprehensive and specialized hospital, Ethiopia, 2018 (n = 353).

Variables
Category
COR (95% CI)
value

Sex
Female
7.72 (4.32, 13.8)
0.002

Male
1.00

Age (years)

0.99 (0.96, 1.02)
0.23

Educational status
Illiterate
1.79 (0.74, 4.34)
0.52

Primary/secondary
0.71 (0.41, 1.21)
0.06

College and above
1.00

Occupational status
Housewife
1.00

Employer
0.32 (0.12, 0.85)
0.02

Merchant
0.94 (0.17, 5.34)
0.19

Pensioners
0.13 (0.05, 0.36)
0.04

Unemployed
0.56 (0.13, 2.29)
0.26

Marital status
Married
1.00

Never married
0.73 (0.33, 1.60)
0.15

Widowed
3.00 (1.02, 8.85)
0.03

Divorced
0.74 (0.37, 1.51)
0.06

WHO clinical stage
Stage I
1.00

Stage II
2.76 (1.37, 5.56)
0.01

Stage III
1.80 (0.91, 3.50)
0.23

Stage IV
1.30 (0.63, 267)
0.17

Duration on ART (months)
<59 months
1.00

60–107 months
0.86 (0.41, 1.84)
0.19

>107 months
1.15 (0.58, 2.31)
0.08

Type of regimen
AZT + 3TC + NPV
1.00

AZT + 3TC + EFV
3.63 (0.77, 17, 11)
0.06

TDF + 3TC + EFV
0.54 (0.28, 1.05)
0.13

TDF + 3TC + NPV
0.94 (0.35, 2.50)
0.21

ABC + 3TC + ATZ
0.18 (0.05, 0.67)
0.04

ABC + 3TC + ATV/r
0.35 (0.12, 0.98)
0.02

Baseline CD4 counts (cells/mm³)
<200
0.22 (0.03, 1.73)
0.17

200–349
0.12 (0.01, 1.00)
0.15

350–499
0.15 (0.02, 1.35)
0.21

>500
1.00

Current CD4 counts (cells/mm³)
<200
0.34 (0.16, 0.73)
<0.001

200–349
0.53 (0.29, 0.99)
0.24

350–499
1.15 (0.61, 2.18)
0.11

>500
1.00

Current viral load (copies/ml)
≤1000 counts
≥1001 counts
1.00
0.50 (0.24, 1.04)
0.16

Body mass index (BMI)
1.23 (1.15, 1.32)
<0.001

Smoked cigarette
Yes
1.46 (0.48, 4.43)
0.18

No
1.00

Consumed alcohol
Yes
0.86 (0.55, 1.34)
0.30

No
1.00

Physical activity
Yes
1.00
0.17

No
0.81 (0.50, 1.29)

Dietary/diversity score
Diversified
1.05 (0.68, 1.61)
0.14

Undiversified
1.00

Depression status
Normal
1.00

Abnormal
0.76 (0.43, 1.35)
0.34

Total cholesterol (TC)
Normal
1.00

Abnormal
0.54 (0.35, 0.84)
0.02

Low-density lipoprotein (LDL)
Normal
1.00

Abnormal
1.83 (1.15, 2.89)
0.01

High-density lipoprotein (HDL)
Normal
1.00

Abnormal
1.62 (0.98, 2.69)
0.23

Total triglyceride (TG)
Normal
1.00

Abnormal
1.41 (0.83, 2.40)
0.12

Blood pressure (BP)
Normal
1.00

Abnormal
1.55 (0.95, 2.54)
0.21

Fasting blood glucose (FBS)
1.002 (0.99, 1.01)
0.16

Table 6: Multivariable binary logistic regression analysis to identify factors associated with central obesity among HIV patients who received ART at armed force comprehensive and specialized hospital, Ethiopia, 2018 (n = 353).

Variables
Category
COR (95% CI)
AOR (95% CI)
value

Sex
Female
7.72 (4.32, 13.8)
85.6 (20.1, 364.6)
<0.001

Male
1.00
1.00

Age (years)

0.99 (0.96, 1.02)
1.01 (0.96, 1.06)
0.610

Educational status
Illiterate
1.79 (0.74, 4.34)
1.31 (0.37, 4.57)
0.673

Primary/secondary
0.71 (0.41, 1.21)
0.48 (0.21, 1.07)
0.074

College and above
1.00
1.00

Occupational status
Housewife
1.00
1.00

Employer
0.32 (0.12, 0.85)
1.84 (0.36, 9.24)
0.46

Merchant
0.94 (0.17, 5.34)
18.8 (1.39, 255)
0.03

Pensioners
0.13 (0.05, 0.36)
1.31 (0.24, 7.10)
0.75

Unemployed
0.56 (0.13, 2.29)
2.13 (0.19, 25.5)
0.55

Marital status
Married
1.00
1.00

Never married
0.73 (0.33, 1.60)
1.67 (0.5, 5.58)
0.405

Widowed
3.00 (1.02, 8.85)
3.32 (0.59, 18.8)
0.175

Divorced
0.74 (0.37, 1.51)
0.31 (0.09, 1.04)
0.058

WHO clinical stage
Stage I
1.00
1.00

Stage II
2.76 (1.37, 5.56)
2.59 (0.80, 8.33)
0.110

Stage III
1.80 (0.91, 3.50)
2.20 (0.75, 6.42)
0.149

Stage IV
1.30 (0.63, 267)
1.09 (0.34, 3.51)
0.879

Duration on ART (months)
<59 months
1.00
1.00

60–107 months
0.86 (0.41, 1.84)
0.49 (0.14, 1.73)
0.269

>107 months
1.15 (0.58, 2.31)
0.35 (0.11, 1.15)
0.084

Type of regimen
AZT + 3TC + NPV
1.00
1.00

AZT + 3TC + EFV
3.63 (0.77, 17, 11)
8.73(1.33, 57.17)
0.024

TDF + 3TC + EFV
0.54 (0.28, 1.05)
0.45(0.16, 1.29)
0.137

TDF + 3TC + NPV
0.94 (0.35, 2.50)
0.51(0.10, 2.47)
0.401

ABC + 3TC + ATZ
0.18 (0.05, 0.67)
0.27(0.02, 2.90)
0.278

ABC + 3TC + ATV/r
0.35 (0.12, 0.98)
0.18(0.03, 0.94)
0.042

Baseline CD4 counts (cells/mm³)
<200
0.22 (0.03, 1.73)
0.4 (0.03, 6.04)
0.508

200–349
0.12 (0.01, 1.004
0.15 (0.01, 2.33)
0.175

350–499
0.15 (0.02, 1.35)
0.12 (0.007, 2.18)
0.152

>500
1.00
1.00

Current CD4 counts(cells/mm³)
<200
0.34 (0.16, 0.73)
0.03 (0.01, 0.160)
<0.001

200–349
0.53 (0.29, 0.99)
0.57 (0.20, 1.63)
0.294

350–499
1.15 (0.61, 2.18)
2.23 (0.84, 5.91)
0.106

>500
1.00
1.00

Current viral load (copies/ml)
≤1000 counts
1.00
1.00

≥1001 counts
0.50 (0.24, 1.04)
1.01 (0.26, 3.96)
0.987

Body mass index (BMI)
1.23 (1.15, 1.32)
3.50 (1.36, 3.89)
<0.001

Smoked cigarette
Yes
1.46 (0.48, 4.43)
1.32 (0.25, 7.12)
0.745

No
1.00
1.00

Consumed alcohol
Yes
0.86 (0.55, 1.34)
1.45 (0.66, 3.17)
0.351

No
1.00
1.00

Physical activity
Yes
1.00
1.00
0.86

No
0.81 (0.50, 1.29)
0.93 (0.399, 2.16)

Dietary diversity score
Diversified
1.05 (0.68, 1.61)
1.38 (0.65, 2.90)
0.40

Undiversified
1.00
1.00

Depression status
Normal
1.00
1.00

Abnormal
0.76 (0.43, 1.35)
0.58 (0.19, 1.74)
0.333

Total cholesterol (TC)
Normal
1.00
1.00

Abnormal
0.54 (0.35, 0.84)
0.39 (0.13, 1.22)

Low-density lipoprotein (LDL)
Normal
1.00
1.00

Abnormal
1.83 (1.15, 2.89)
1.43 (0.46, 4.45)
0.539

High-density lipoprotein (HDL)
Normal
1.00
1.00

Abnormal
1.62 (0.98, 2.69)
1.15 (0.46, 2.84)
0.763

Total triglyceride (TG)
Normal
1.00
1.00

Abnormal
1.41 (0.83, 2.40)
1.59 (0.66, 3.79)
0.298

Blood pressure (BP)
Normal
1.00
1.00

Abnormal
1.55 (0.95, 2.54)
2.53 (1.13, 5.67)
0.024

Fasting blood glucose (FBS)
1.002 (0.99, 1.01)
1.004 (0.99, 1.02)
0.514

value <0.05 (statistically significant association); 1.00: reference category. Hosmer and Lemeshow test ( value: 0.57).

4. Discussion

In this study, the prevalence of central obesity was 71.7% (95% CI: 67%–76.4%). This finding is higher than those in studies conducted elsewhere, for instance, 4% in the United States [10], 12.6% in Tanzania [11], 36.5% in Malaysia [12], and 45.7% in Brazil [13]. This discrepancy may be due to the type used to measure central obesity and sample size variation, in which the current study utilized a large sample size and WHR, which early detected central obesity among HIV-infected population.

The present study also revealed that sex, occupational status, type of ART regimen, current CD4 counts, BMI, and abnormal blood pressure were associated with central obesity.

The odds of central obesity were higher among females compared to males. This finding is supported by studies conducted in Brazil [14], Nigeria [25], and Kenya [26]. This could be expounded by HIV-infected women who had a higher waist-to-hip ratio (WHR) than the control population [7]. Also, men were more likely to progress to overweight and women to obesity [9].

Besides, women have substantially more total adipose tissue than men, and these whole‐body sex differences are complemented by major differences in tissue distribution [27].

The odds of central obesity were higher among merchants than among housewives. This may be related to having a high-income result in sedentary life which was associated with central obesity [25].

The study further showed that increased BMI results in increased odds of central obesity. This finding is evidenced by studies done in Malaysia [12]. This could be explained by changes in the waist and hip circumferences correlated directly with weight changes [27].

In this study, a higher CD4 count increased the odds of central obesity. This finding is similar to those in other studies conducted elsewhere [14, 25]. However, a systematic review showed that central obesity is evident among patients with CD4 counts <350 cells/mm³ but not among patients with higher CD4 counts [17]. The result found reaffirms the hypothesis that being overweight is linked to a better immune status, but since the studies are controversial, investigation in future research is warranted.

Abnormal blood pressure results in higher odds of central obesity. This finding is in line with studies done in Cameroon [28] and Indonesia [29]. This could be explained by having a close association between hypertension and dyslipidemia. Studies showed that hypertensive patients compared with normotensives have higher serum levels of TC, TG, and LDL, while HDL levels were lower [29].

Furthermore, the odds of central obesity were higher among respondents taking AZT + 3TC + EFV compared to AZT + 3TC + NPV-based ART regimen. [30]. Likewise, the odds of central obesity were higher among respondents taking AZT + 3TC + EFV compared to AZT + 3TC + NPV-based ART regimen. However, participants taking ABC + 3TC + ATV/r-based regimen were 82% protective against central obesity compared to AZT + 3TC + NPV-based ART regimen. Similar findings were found in Silchar [31]. Efavirenz (EFV) and zidovudine (AZT) have already been reported as causative of metabolic syndrome by increased TG and LDL-c levels but decreased HDL-c levels [32].

4.1. Strength and Limitation of the Study

The strength of the present study is that central obesity is assessed using WHR, which is useful in early detecting possible signs of excess fat deposition in those infected with HIV. Although findings in this study are useful for policy, there are some noteworthy limitations. For example, the data were collected in a cross-sectional study; therefore, our study may not assign causation.

5. Conclusions

From the findings of the study, it is possible to conclude that central obesity is a huge public health problem among the HIV-infected population in the study area. Being female, increased BMI, low CD4 count, AZT + 3TC + EFV, ABC + 3TC + ATV/r-based regimen, and abnormal blood pressure were associated with central obesity. Therefore, adequate attention must be paid to primary and secondary control of these factors to reduce the prevalence of abdominal obesity among HIV-infected patients.

Data Availability

The dataset used for this study cannot be shared and, in the future, interested parties may request approval to access the data by writing to Jimma University Institutional Review Board.

Conflicts of Interest

The authors confirm that this research is their original paper and that there are no conflicts of interest in this work.

Authors’ Contributions

AK conceived the research idea, performed data analysis and interpretation, and wrote and reviewed the manuscript. MA, MST, and KHA reviewed and approved the final paper. All authors contributed to data analysis, drafting, and revising the paper and agreed to be accountable for all aspects of the work.

Acknowledgments

The authors would like to acknowledge Jimma University, Institute of Health, and armed force comprehensive and specialized hospital for funding and sponsoring this study. The authors would also like to thank data collectors and study participants. The study was fully funded by Jimma University, Institute of Health, and Faculty of Public Health and armed force comprehensive and specialized hospital.

References

C. A. Sabin, “Do people with HIV infection have a normal life expectancy in the era of combination antiretroviral therapy?” BMC Medicine, vol. 11, pp. 1–7, 2013.

FHAPCO, HIV Prevention in Ethiopia National Road Map 2018–2020, Federal HIV/AIDS Prevention and Control Office, Addia Ababa, 2020.

T. Tate, A. L. Willig, J. H. Willig et al., “HIV infection and obesity: where did all the wasting go,” Antiviral Therapy, vol. 17, no. 7, pp. 1281–1289, 2013.

C. U. Nduka, O. A. Uthman, P. K. Kimani, and S. Stranges, “Body fat changes in people living with HIV on antiretroviral therapy,” AIDS Reviews, vol. 18, pp. 198–211, 2016.

K. Shah, A. P. Alio, W. J. Hall, and A. E. Luque, “The physiological effects of obesity in HIV-infected patients AIDS & clinical research,” Journal of AIDS & Clinical Research, vol. 3, no. 4, 2012.

A. M. Thompson-Paul, S. C. Wei, C. L. Mattson, M. Robertson, A. C. Hernandez-Romieu, and T. K. Bell, “Obesity among HIV-infected adults receiving medical care in the United States: data from the cross-sectional medical monitoring project and national health and nutrition examination survey,” Medicine, vol. 94, no. 27, pp. 1–10, 2015.

S. E. Dolan, C. Hadigan, K. M. Killilea et al., “Increased cardiovascular disease risk indices in in HIV-infected women,” Journal of Acquired Immune Deficiency Syndromes, vol. 39, no. 1, pp. 44–54, 2005.

J. E. Justman, D. R. Hoover, Q. Shi et al., “Longitudinal anthropometric patterns among HIV-infected and—uninfected women jessica,” Journal of Acquired Immune Deficiency Syndromes, vol. 47, no. 3, pp. 312–319, 2015.

L. H. M. Leite and A. B. D. M. M. Sampaio, “Progression to overweight, obesity and associated factors after antiretroviral therapy initiation among brazilian persons with HIV/AIDS,” Nutricion Hospitalaria, vol. 25, no. 4, pp. 635–640, 2010.

M. Noorhasan, D. R. Drozd, C. Grunfeld et al., “Associations between at-risk alcohol use, substance use, and smoking with lipohypertrophy and lipoatrophy among patients living with HIV,” AIDS Research and Human Retroviruses, vol. 33, no. 6, pp. 534–545, 2017.

M. Njelekela, R. Mpembeni, A. Muhihi, N. Ulenga, E. Aris, and D. Kakoko, “Lipodystrophy among HIV-infected patients attending care and treatment clinics in dar es salaam,” AIDS Research and Treatment, vol. 2017, Article ID 3896539, 10 pages, 2017.

N. Hejazi, “Factors associated with abdominal obesity among HIV-infected adults on antiretroviral therapy in Malaysia,” Global Journal of Health Science, vol. 2, no. 2, pp. 20–31, 2010.

A. A. Florindo and O. Latorre, “Central obesity and dietary intake in HIV/AIDS patients obesidade abdominal e consumo alimentar em portadores de HIV/,” Revista de Saúde Pública, vol. 40, no. 4, pp. 634–640, 2006.

A. d. C. O. Castro, E. A. Silveira, M. d. O. Falco, M. W. Nery, and M. D. Turchi, “Overweight and abdominal obesity in adults living with HIV/AIDS,” Revista da Associação Médica Brasileira, vol. 62, no. 4, pp. 353–360, 2016.

S. Khetsiwe, S. Masuku, J. T. Gwegweni, and B. Sartorius, “HIV and antiretroviral therapy—induced metabolic syndrome in people living with HIV and its implications for care: a critical review,” Journal of Diabetology, vol. 10, no. 2, p. 41, 2019.

S. Kumar and K. Samaras, “The impact of weight gain during HIV treatment on risk of pre-diabetes, diabetes mellitus, cardiovascular disease, and mortality,” Frontiers in Endocrinology, vol. 9, pp. 705–714, 2018.

J. S. Neves, V. Guerreiro, D. Carvalho, and R. Serrão, “Metabolically healthy or metabolically unhealthy obese HIV-infected patients: mostly a matter of age?” Frontiers in Endocrinology, vol. 9, pp. 1–18, 2018.

J. E. Lake, “The fat of the matter: obesity and visceral adiposity in treated HIV infection,” Current HIV, vol. 14, no. 6, pp. 211–219, 2017.

M. Papagianni and K. Tziomalos, “Obesity in patients with HIV infection: epidemiology, consequences and treatment options,” Expert Review of Endocrinology and Metabolism, vol. 11, no. 5, pp. 395–402, 2016.

J. L. Finkelstein, P. Gala, R. Rochford, M. J. Glesby, and S. Mehta, “HIV/AIDS and lipodystrophy: implications for clinical management in resource-limited settings,” Journal of the International AIDS Society, vol. 18, no. 1, p. 19033, 2015.

C. A. Dimala, R. C. Ngu, B. M. Kadia, F. L. Tianyi, and S. P. Choukem, “Markers of adiposity in HIV/AIDS patients: agreement between waist circumference, waist-to-hip ratio, waist-to-height ratio and body mass index,” PLoS One, vol. 13, no. 3, Article ID e0194653, 2018.

S. O. Onesi and U. E. Ignatius, “Metabolic syndrome: performance of five different diagnostic criterias,” Indian Journal of Endocrinology and Metabolism, vol. 18, no. 4, pp. 496–501, 2014.

K. G. M. M. Alberti, P. Zimmet, and J. Shaw, “Metabolic syndrome-a new world-wide definition. a consensus statement from the international diabetes federation,” Diabetic Medicine, vol. 23, no. 5, pp. 469–480, 2006.

WHO, The WHO STEPwise Approach to Chronic Disease Risk Factor Surveillance, WHO, Geneva, Switzerland, 2005.

E. Stomdfacpfac, J. S. Kaufman, and A. F. Bella, “Central obesity in Africans: anthropometric assessment of abdominal adiposity and its predictors in urban Nigerians,” Journal of the National Medical Association, vol. 110, no. 5, pp. 519–527, 2018.

A. Saito, M. Karama, and Y. Kamiya, “HIV infection, and overweight and hypertension: a cross-sectional study of HIV-infected adults in Western Kenya,” Tropical Medicine and Health, vol. 48, p. 31, 2020.

W. Expert, Waist Circumference and Waist-Hip Ratio Report of a WHO Expert Consultation, WHO, Geneva, Switzerland, 2008.

R. C. Ngu, S. P. Choukem, C. A. Dimala, and J. N. Ngu, “Prevalence and determinants of selected cardio—metabolic risk factors among people living with HIV/AIDS and receiving care in the South West regional hospitals of cameroon: a cross—sectional study,” BMC Research Notes, vol. 11, no. 1, p. 305, 2018.

Y. Nurdiantami, K. Watanabe, E. Tanaka, J. Pradono, and T. Anme, “Association of general and central obesity with hypertension,” Clinical Nutrition, vol. 37, no. 4, pp. 1259–1263, 2017.

K. N. Choudhury, A. K. Mainuddin, M. Wahiduzzaman, and S. M. S. Islam, “Serum lipid profile and its association with hypertension in Bangladesh,” Vascular Health and Risk Management, vol. 10, pp. 327–332, 2014.

D. S. K. Abhijit Swami, “A study of metabolic syndrome in HIV patients treated with NNRTI based antiretroviral therapy,” Scholars Journal of Applied Medical Sciences, vol. 5, pp. 827–834, 2017.

A. A. Paula, M. C. N. Falcão, and A. G. Pacheco, “Metabolic syndrome in HIV-infected individuals: underlying mechanisms and epidemiological aspects,” AIDS Research and Therapy, vol. 10, no. 1, p. 32, 2013.