Undernutrition and Associated Factors Among Adults on Second-Line Antiretroviral Therapy in Debark,Ethiopia: A Cross-Sectional Study

Abstract

Background/Objectives

Undernutrition remains a major public health challenge among people living with HIV, particularly in low-income settings, where it adversely affects treatment outcomes, immunity, and survival, where it contributes to poor treatment outcomes, increased susceptibility to opportunistic infections, and higher mortality. Although several studies in Ethiopia have examined undernutrition among adults receiving first-line antiretroviral therapy (ART), evidence focusing specifically on individuals receiving second-line ART is limited. Therefore, this study aimed to assess the prevalence of undernutrition and identify factors associated with undernutrition among adults living with HIV receiving second-line ART in public health facilities of Debark town, Ethiopia.

Methods

An institution-based cross-sectional study was conducted from June 1 to June 30, 2025, among adults living with HIV receiving second-line ART in public health facilities of Debark town, Ethiopia. Participants were selected using a simple random sampling technique based on medical registration numbers. Data were collected using a structured interviewer-administered questionnaire and medical record review checklist adapted from previous studies. Nutritional status was assessed using body mass index (BMI). Data were entered into EpiData version 3.1 and analyzed using STATA version 14. Bivariable and multivariable logistic regression analyses were performed to identify factors associated with undernutrition.

Results

Undernutrition, defined as a BMI of < 18.5 kg/m², was observed in 24% of the participants (95% confidence interval (CI) [20-28]). Factors significantly associated with undernutrition included poor ART adherence (adjusted odds ratio (AOR) = 4.10; 95% CI [1.64-10.27]), ART duration ≤24 months (AOR = 9.20; 95% CI [3.43-24.65]), presence of opportunistic infections (AOR = 2.35; 95% CI [1.11-4.96]), low dietary diversity score (AOR = 2.19; 95% CI [1.19-4.04]), moderate household food insecurity (AOR = 2.17; 95% CI [1.16-4.09]), and severe household food insecurity (AOR = 2.53; 95% CI [1.17-5.46]).

Conclusion and recommendations

Plain Language Summary Title

Poor Nutrition and Related Factors among Adults Living with HIV Who Are Taking Second-Line HIV Treatment in Public Health Facilities in Debark Town, Ethiopia

Plain Language Summary

People living with HIV need good nutrition to stay healthy and to make their HIV treatment work well. Some adults who are taking second-line HIV medicines may not be getting enough nutritious food, which can affect their health and treatment outcomes. This study aims to find out how common poor nutrition is among adults living with HIV who are receiving second-line treatment in public health facilities in Debark Town, Ethiopia. It will also look at factors that may be linked to poor nutrition, such as food availability, illness, treatment-related side effects, and social or economic conditions. Information will be collected from adult patients through interviews, review of medical records, and basic body measurements such as weight and height. The findings from this study will help health workers and decision-makers understand the nutrition-related challenges faced by people living with HIV on second-line treatment. This information can be used to improve nutrition support, treatment care, and overall health services for these patients.

Keywords

undernutrition adult PLWHA Debark Ethiopia

Introduction

HIV remains a critical public health issue worldwide. In 2021, around 38.4 million people (33.9-43.8 million) were living with HIV, with approximately 1.5 million (1.1-2.0 million) new infections reported globally. Of those living with HIV, about 75% (28.7 million people) were receiving antiretroviral therapy (ART). In Africa, an estimated 25.6 million individuals (23.4-28.6 million) were living with HIV, and nearly 860,000 (660,000-1.2 million) people acquired HIV for the first time that year. Among people living with HIV (PLHIV) in the region, 88% (80→98%) knew their HIV status, and 78% (72-88%) were on treatment.^1,2 Ethiopia is among the Sub-Saharan African (SSA) countries most affected by HIV,³ previous report estimated that 609,349 PLHIV/acquired immune deficiency syndrome (AIDS) (PLWHA), and 10,567 were Newly HIV infected in 2022.⁴

HIV infection, nutritional status, and immune function are closely interconnected, with nutrition playing a significant role in the progression of HIV.⁵ The relationship between HIV and malnutrition is complex and bidirectional, as HIV can impair the body's ability to absorb, store, and utilize nutrients effectively. This disruption often leads to nutrient deficiencies, weakened immunity, and an increased susceptibility to infections.^6,7 Under nutrition among PLHIV is a global concern. For instance, a study in Nepal reported that 18.3% of HIV-infected individuals had a body mass index (BMI) below 18.5 kg/m².⁸

SSA faces a dual burden of malnutrition, with both under nutrition and rising rates of obesity and diet-related noncommunicable diseases.⁹ Malnutrition is highly prevalent among HIV-infected adults enrolled in care within the region. Country-specific studies have reported under nutrition prevalence rates of 19% in Tanzania, 10% in Zimbabwe, and 19% in Senegal.⁶ Similarly, in Ethiopia, under nutrition among HIV-positive adults is a significant problem. A cross-sectional study in Nekemte town indicated that 24% of adults living with HIV were undernourished.¹⁰

Multicenter studies in Ethiopia have also highlighted the burden of under nutrition among ART patients, with prevalence rates of 19.1% in selected health facilities in Addis Ababa and 34% at Jimma Medical Centre.⁶ Several factors have been associated with under nutrition in PLHIV, including advanced clinical stage, socioeconomic status, and food aid availability, as shown in studies conducted in the Jimma zone.¹¹ In Arba-Minch town, a study among adults on first-line ART identified current substance use, duration on ART, advanced World Health Organization (WHO) clinical stage, CD4 count below 350 cells/mm³, and active tuberculosis as significant predictors of under nutrition.¹²

The Ethiopian Ministry of Health has made substantial progress in HIV prevention, diagnosis, treatment, and care, including management of opportunistic infections, transforming HIV into a manageable chronic condition and enabling PLHIV to live longer, healthier lives.¹³ However, malnutrition continues to affect many individuals living with HIV in Ethiopia, and the government has incorporated nutritional support, including ready-to-use therapeutic foods, into national HIV treatment guidelines based on disease stage.¹⁴ Additionally, adverse effects of second-line ART drugs, such as Atazanavir—reported to cause nausea in 4% to 14% and diarrhea in 3% to 11% of patients—can reduce food intake and nutrient absorption. Conversely, malnutrition itself can affect drug bioavailability.¹⁵

Undernutrition remains a major public health challenge among PLHIV, particularly in low-income settings, where it adversely affects treatment outcomes, immunity, and survival, where it contributes to poor treatment outcomes, increased susceptibility to opportunistic infections, and higher mortality. Although several studies in Ethiopia have examined undernutrition among adults receiving first-line ART, evidence focusing specifically on individuals receiving second-line ART is limited. To the best of our knowledge, there is limited published evidence addressing the prevalence of undernutrition and its associated factors among adults on second-line ART in Ethiopia, and routine nutritional surveillance in this population remains inadequate. Given the growing number of patients transitioning to second-line therapy due to treatment failure and drug resistance, understanding the magnitude and determinants of undernutrition in this group is essential for improving clinical management and informing targeted nutritional interventions. Therefore, this study aimed to assess the prevalence of undernutrition and identify factors associated with undernutrition among adults living with HIV receiving second-line ART in public health facilities of Debark town, Ethiopia.

Conceptual Framework Description

This study was guided by a conceptual framework adapted from existing literature on HIV, nutrition, and public health models. The framework illustrates the hypothesized relationships between sociodemographic characteristics, household food security, clinical factors, and dietary practices, and how these factors interact to influence undernutrition among adults receiving second-line ART. Sociodemographic and household-level factors act as distal determinants affecting dietary diversity, treatment adherence, and susceptibility to opportunistic infections. These intermediate factors directly influence nutritional status, leading to undernutrition as the primary outcome. The framework also identifies potential intervention points, including nutritional counseling, food support, adherence support, and early detection and management of opportunistic infections (Figure 1).

Figure 1.

Conceptual framework obtained from different works of literatures.

Material and Methods

Study Design and Period

An institution-based cross-sectional study was conducted from June 1 to June 30, 2025, among adults living with HIV receiving second-line ART in public health facilities of Debark town, Ethiopia. The reporting of this study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for cross-sectional studies¹⁶ (Supplemental File S1).

Study Area

The study was conducted in Debark Town, located in the North Gondar Zone of the Amhara Regional State, Ethiopia. Debark is approximately 100 km from Gondar, 280 km from Bahir Dar, and 841 km from Addis Ababa. Geographically, the town lies at a latitude of 13°08′00″ N and a longitude of 37°54′00″ E, with an elevation of 2850 m above sea level. It is the nearest town to Simien Mountains National Park and is bordered by Dabat to the south, Tegede to the west, Adirkay to the north, and Janamora to the east, covering an area of 1461.18 km². According to the Central Statistics Agency of Ethiopia, Debark has an estimated population of 227,526, with 119,887 males and 107,639 females. In terms of health services, the town has one hospital and one health center, with the hospital, established in 1997 GC, serving as a referral center for the surrounding districts.^17,18

Source Population

The study included all adult HIV-positive clients who were enrolled in chronic HIV care and receiving second-line ART at public health facilities in Debark town. Specifically, the population comprised adults attending the ART and PMTCT clinics who met these criteria.

Inclusion and Exclusion Criteria

The adult HIV-positive clients who had been receiving second-line ART and had completed at least 6 months of follow-up for their treatment were included in the study. Clients were excluded if they were unable to communicate, had kyphoscoliosis (which could affect accurate height measurement), or had incomplete medical records.

Sample Size Determination

The required sample size was calculated using Epi Info statistical software version 7.2. A single population proportion formula was applied, assuming a 95% confidence level, a 5% margin of error, and a 10% nonresponse rate. Since there are no previous studies reporting the prevalence of malnutrition among PLHIV receiving second-line ART in Ethiopia, a proportion of 50% was used to maximize the sample size.

Sample size calculation for proportion of malnutrition.

\begin{aligned} n = (Z α / 2) 2 * p (1 - p) \\ (d) 2 \\ n = the initial sample size \\ Z α / 2 = standardized normal distribution value for the 95 % CI = 1.96 \\ P = proportion of previous studies (50 %) \\ d = margin of error 5 % \\ \frac{n = (1.96) 2 \times 0.5 (1 - 0.5)}{(0.05) 2} = 384 \end{aligned}

The final calculated sample size was 384. After adding 10% of nonresponse rate, the final sample size will be 422.

Sampling Procedure

Study participants from each public health facility were selected using a proportional allocation method based on caseloads. Participants were chosen through a simple random sampling technique after compiling a list of Medical Registration Numbers (MRN).

Variables of the Study

Dependent Variables

Undernutrition (yes/no)

Independent Variables

Sociodemographic and Economic Variables: Gender, age, marital status, religion, educational level, place of residence, occupation, and wealth index.

Clinical Factors: Duration of ART, CD4 count, viral load, WHO staging, regimen type, opportunistic Infections, ART adherence, functional status.

Behavioral Factor: Alcohol use, khat chewing, cigarette smoking, depression.

Nutritional Factors: Nutritional counseling, food supplement/AID.

Operational Definitions

Undernutrition: Nutritional status was assessed using BMI, calculated as weight in kilograms divided by height in meters squared (kg/m²). Undernutrition was defined as BMI < 18.5 kg/m², normal nutritional status as BMI 18.5 to 24.9 kg/m², overweight as BMI 25.0 to 29.9 kg/m², and obesity as BMI ≥ 30.0 kg/m², in accordance with WHO classification. BMI was used as a standardized and widely accepted anthropometric measure for assessing adult nutritional status in clinical and population-based studies.¹⁹

Second-Line ART Regimens: Prescribed when patients experience treatment failure on first-line regimens; these consist of a boosted protease inhibitor combined with 2 nucleoside reverse transcriptase inhibitors, according to the Ethiopian ART Guideline.²⁰

Functional Status: Functional status was assessed using the WHO functional status classification for HIV care. Participants were categorized as working (able to perform usual work inside or outside the home), ambulatory (able to perform activities of daily living but not able to work), or bedridden (unable to perform activities of daily living). Ambulatory status indicates reduced functional capacity but does not necessarily imply terminal illness.²¹

PLWHA: Refer to people who have undertaken an HIV test and have been declared positive whether or not they show any symptoms of infection or AIDS disease.

Opportunistic Infections: If the HIV-infected adults on ART are diagnosed with at least one or more opportunistic infections or multiple infections are reported on their medical record.

Poor Drug Adherence: Taking less than 85% of doses per month (≥9 dose missed per month for those who are taking twice per day and ≥5 doses per month for those who are taking once per day).²²

Fair Drug Adherence: Taking 85% to 94% of dose per month (4-9 doses missed per month for those who are taking twice per day and 3-4 dose per month for those who are taking once per day).²²

Good Drug Adherence: Taking greater than or equal to 95% of doses per month (<3 dose missed per month for those who are taking twice per day and <2 doses per month for those who are taking once per day).²²

Alcohol Drinker: Excessive alcohol consumption includes binge drinking (4 or more drinks for women and 5 or more drinks for men within about 2 h) and heavy drinking (8 or more drinks a week for women and 15 or more drinks a week for men).²³

Light Smoker: Someone who smokes less than 10 cigarettes per day.²⁴

Heavy Smoker: Someone who smokes a pack (20 cigarettes) a day or more.²⁵

Food Security Status: Assessed using the Household Food Insecurity Access Scale, which measures three domains: anxiety and uncertainty about food supply, insufficient quality (variety and preference of foods), and inadequate food intake with its physical consequences. A 4-week recall period was used, asking respondents whether each condition occurred in the past four weeks. If “yes,” the frequency was recorded as rarely (1-2 times), sometimes (3-10 times), or often (>10 times). Based on responses, households were classified into four categories: food secure, mildly food insecure, moderately food insecure, and severely food insecure.²⁶

Dietary Diversity Score (DDS): Collected by asking participants to list all foods consumed in the previous 24 h. Reported items were grouped into 12 food groups. Using 5 food groups as the minimum dietary diversity threshold, participants with DDS < 5 were considered to have poor dietary diversity, while those with DDS ≥ 5 were considered to have good dietary diversity.²⁷

Data Collection Tools and Procedures

Data were collected using a structured questionnaire and checklists adapted from previous literature. The questionnaire covering sociodemographic and economic information, clinical characteristics, behavioral factors, and nutrition-related variables. Nutrition support, nutritional counseling, and behavioral factors were assessed through interviewer-administered questionnaires, while secondary data including WHO clinical stage, adherence status, functional status, viral load, CD4 count, ART regimen and duration, and disclosure status were extracted from patients’ medical records (ART follow-up charts) and registration books.

Three trained nurses (MSc/MPH/BSc) served as data collectors, and one MPH supervised the process. Training was provided to both data collectors and the supervisor before data collection commenced. Patient charts were selected from ART logbooks using a lottery method after listing MRN or Unique ART Numbers as a sampling frame from clients receiving second-line ART at the selected public health facilities (one health center and one hospital) in Debark town. Data collection continued until the target sample size was reached. To avoid duplicate data collection, a unique code agreed upon by the data collectors was assigned to each participant.

Anthropometric Measurement

To have information on the individuals’ BMI, Anthropometric measurement was used. Weight of the study participants was measured to the nearest 0.1 kg of a beam balance with graduation 0.1 kg and measuring range up to 160 kg. Weight was measured with light clothing and no shoes. Calibration was done before weighing each participant by setting it to zero. Weighing scale also checked against a standard weight for its accuracy on daily basis. Height of the participant was measured using Seca vertical height standing upright in the middle of board. The participant's head, shoulders, buttocks, knees and heels touch's against the vertical board.

Drug Adherence was assessed based on the Ethiopian Ministry of Health guidelines, which define poor adherence as missing >9 doses per month for those taking medicine twice daily or >5 doses for those taking medicine once daily (<85% adherence). Fair adherence is classified as 85% to 94%, corresponding to missing 4 to 9 doses per month for twice daily users and 3 to 4 doses for once daily users. Good adherence is considered ≥95%, equating to missing <3 doses per month for those taking medication twice daily and <2 doses for those taking medication once daily.²⁸ ART-Related Side Effects were assessed using patient self-report and medical record review. Participants were asked about the presence of common side effects experienced during ART use, including nausea, vomiting, diarrhea, loss of appetite, fatigue, and dizziness. These variables were included in the analysis to examine their association with nutritional status. CD4 Cell Count was used to assess immunological status. Participants with a CD4 count of < 200 cells/µL were classified as having AIDS, while those with a CD4 count ≥ 200 cells/µL were classified as non-AIDS, based on the WHO immunological classification system.²⁹

Household Socioeconomic Status was assessed using a wealth index constructed based on ownership of selected household assets and housing characteristics. Principal component analysis was used to generate a composite wealth score, which was then categorized into tertiles (low, middle, and high wealth status). The wealth index serves as a proxy measure of household socioeconomic position and has been widely used in settings where direct income or expenditure data are difficult to obtain.³⁰ Clinical Stage was determined using the WHO clinical staging system for HIV/AIDS, which classifies HIV infection into 4 stages: Stage I (asymptomatic), Stage II (mild symptoms), Stage III (advanced disease), and Stage IV (AIDS-defining conditions). AIDS status was additionally defined immunologically as a CD4 count < 200 cells/µL, in accordance with WHO guidelines.²⁹

Participants’ height was measured using a standard measuring scale. They removed their shoes, stood erect, and looked straight ahead in the horizontal plane. The occiput, shoulders, buttocks, and heels were positioned against the measuring board, and height was recorded to the nearest 0.01 cm.³¹

Three data collectors (clinical nurses) and 1 MPH supervisor were recruited and 2 days intensive training was given. The data collection process was followed daily by the supervisor and principal investigators.

Data Quality Control

Data quality was ensured through comprehensive training of data collectors and the supervisor on the overall data collection procedures. The questionnaire was initially prepared in English, translated into Amharic, and then back-translated into English by language experts to maintain consistency. The data collection checklist was pretested to assess clarity, completeness, and internal consistency of the tool. Detailed training was provided to the data collectors and supervisor on the contents of the questionnaire and standardized data collection procedures, with each component thoroughly discussed. Throughout the data collection period, the supervisor closely monitored the process to ensure adherence to the protocol and data completeness.

Data Management and Analysis

The data were checked for completeness and consistency before being entered into EpiData version 3.1 and subsequently exported to STATA version 14 for analysis. Descriptive statistics were used to summarize the data and were presented using frequency tables, pie charts, and graphs. Both bivariate and multivariable logistic regression analyses were conducted to identify factors associated with under nutrition among PLHIV/AIDS (PLWHA). Variables with a P-value ≤ .20 in the bivariate analysis were included in the multivariable model to control for potential confounding effects. Model fitness was assessed using the Hosmer–Lemeshow goodness-of-fit test (P = .6326), and multicollinearity was evaluated using the variance inflation factor. In the multivariable analysis, variables with a P-value < .05 at a 95% confidence interval were considered statistically significant.

Results

Sociodemographic and Economic Factors

We recruited a total of 410 respondents in this study with the response rate of 97%. The majority of the participants (59%) were females. More than one-third of respondents (46%) found in the age group of 30 to 44 years. Regarding their educational status 28% of respondents had attended primary school. Regarding their employment status, 21% of the participants were Merchant. Most of the respondents (89%) were lived in urban (Table 1).

Table 1.

Sociodemographic and Economic Factors Among Adult PLWHA Receiving Second Line Antiretroviral Treatment in Public Health Facilities of Debark Town, Ethiopia 2025 (n = 410).

Variable	Category	Frequency (n)	Percent (%)
Sex	Female	241	59
	Male	169	41
Age group	18-29 years	99	24
	30-44 years	188	46
	45 and above	123	30
Marital status	Single	95	23
	Married	204	50
	Divorced	69	17
	Widowed	42	10
Religion	Orthodox	368	90
	Muslim	36	9
	Protestant	6	1
Education	Unable to read and write	54	13
	Able to read and write	92	22
	Primary school	113	28
	Secondary school	96	23
	College and above	55	13
Residence	Urban	366	89
	Rural	44	11
Occupation	Government employee	75	18
	Daily laborer	35	9
	Farmer	14	3
	Housewife	81	20
	Merchant	87	21
	Others*	76	19
Wealth index	Poorest	191	47
	Middle	128	31
	Richer	17	4
	Richest	74	18

*Students, jobless, and so on.

Clinical, Behavioral and Nutrition-Related Factors

More than half of patients (83%) found in Stage-I WHO clinical staging. Two hundred thirteen (52%) patients have a current CD4 cell count of 200 to 500 (cell/mm³). From the total study participants, 50 (12%) of participants have developed an opportunistic infection. Ninety-seven percent out of the total participants were working regarding their functional status. From the study participants, 1% of them chew khat, and 24% and 1% drink alcohol and smoke cigarette, respectively. Large numbers of the respondents (59%) were living under food secured, whereas 22% were under moderate food insecurity, 6% under mild foods insecurity, and 12% were living under severe food insecurity. 21% of the study participants were under low dietary diversity (Table 2).

Table 2.

Clinical, Behavioral and Nutrition-Related Factors Among Adult PLWHA Receiving Second Line Antiretroviral Treatment in Public Health Facilities of Debark Town, Ethiopia 2025 (n = 410).

Variable	Category	Number (n)	Percent (%)
CD4 count	< 200	111	30
	≥ 200	299	70
Opportunistic infection	Yes	50	12
	No	360	88
Functional status	Working	399	97
	Ambulatory	11	3
ART adherence	Good	320	78
	Fair	62	15
	Poor	28	7
ART side effect	Yes	26	6
	No	384	94
ART duration	≤24 months	27	7
	24+ months	383	93
Get HIV-related food aid from organizations	Yes	203	49
	No	208	50
Attended dietary counseling session	Yes	66	16
	No	344	84
Dietary diversity	Low	86	21
	High	324	79
Household food security status	Secured	242	59
	Mild	26	6
	Moderate	91	22
	Severe	51	12
Alcohol consumption	Yes	98	24
	No	312	76
Cigarette smoking	Yes	5	1
	No	405	99
Khat chewing	Yes	4	1
	No	406	99
Depression	Yes	6	1
	No	404	99

Abbreviation: PLWHA: people living with HIV/AIDS.

Prevalence of Under Nutrition

Undernutrition, defined as a BMI of < 18.5 kg/m², was observed in 24% of the participants (95% confidence interval (CI) [20-28]). The mean (± SD) BMI of the study population was 21.04 ± 3.62 kg/m ² .

Factors Associated With Under Nutrition

Multivariable logistic regression analysis was conducted to identify independent predictors of undernutrition. Variables that showed an association with the outcome in the bivariate logistic regression analysis were included in the multivariable model. After adjusting for potential confounders, poor ART adherence was significantly associated with undernutrition, with patients exhibiting poor adherence being more than four times more likely to be undernourished compared to those with good adherence (adjusted odds ratio (AOR) = 4.10; 95% CI [1.64-10.27]).

Participants who had been on ART for less than 24 months were over 9 times more likely to experience under nutrition compared with those who had been on ART for 24 months or longer (AOR = 9.20; 95% CI [3.43-24.65]). In addition, the presence of opportunistic infections significantly increased the likelihood of undernutrition, as affected patients were more than twice as likely to be undernourished compared to those without such infections (AOR = 2.35; 95% CI [1.11-4.96]).

Regarding household food security, individuals from moderately food-insecure households had more than twice the odds of undernutrition (AOR = 2.17; 95% CI [1.16-4.09]), while those from severely food-insecure households had an even higher likelihood of under nutrition (AOR = 2.53; 95% CI [1.17-5.46]), compared to food-secure households. Furthermore, participants with low dietary diversity scores were over 2 times more likely to be undernourished than those with adequate dietary diversity (AOR = 2.19; 95% CI [1.19-4.04]) (Table 3).

Table 3.

Bivariable and Multivariable Logistic Regression Model Predicting the Likelihood of Undernutrition and Associated Factors Among Adult PLWHA Receiving Second Line Antiretroviral Treatment in Public Health Facilities of Debark Town, Ethiopia 2025.

Variable	Under Nutrition		COR [95% CI]	AOR [95% CI]
Variable	Yes	No	COR [95% CI]	AOR [95% CI]
Age
18 to 29	38	61	2.01 [1.12-3.60]	1.52 [0.76-3.05]
30 to 44	31	157	0.64 [0.36-1.12]	0.58 [0.30-1.11]
45+	29	94	1	1
Residence
Urban	92	274	2.12 [0.87-5.19]	1.87 [0.59-5.96]
Rural	6	438	1	1
ART adherence
Fair	21	41	2.08 [1.15-3.78]	1.75 [0.86-3.55]
Poor	14	14	4.07 [1.85-8.99]	4.10 [1.64-10.27]
Good	63	257	1	1
Clinical stage
Stage II	22	49	1.57 [0.88-2.80]	0.73 [0.34-1.57]
Stage I	76	263	1	1
Nutritional support
No	58	150	1.56 [0.98-2.48]	1.04 [0.60- 1.82]
Yes	40	162	1	1
Opportunistic infection
Yes	24	26	3.56 [1.93-6.57]	2.35 [1.11-4.96]
No	74	286	1	1
ART duration
≤24 months	18	9	7.57 [3.27-17.49]	9.20 [3.43-24.65]
24+ months	80	303	1	1
Dietary diversity
Low	32	54	2.31 [1.38-3.87]	2.19 [1.19- 4.04]
High	66	258	1	1
Food security
Mild food insecure	5	201	1.16 [0.41-3.27]	0.90 [0.27-3.05)
Moderate food insecure	32	21	2.65 [1.54-4.58]	2.17 [1.16-4.09]
Severe food insecure	20	59	3.16 [1.64-6.08]	2.53 [1.17-5.46]
Food secure	41	31	1	1
Side effect
No	297	87	2.50 [1.10- 5.64]	2.29 [0.87- 6.04]
Yes	15	11	1	1
Smoking
Yes	3	2	4.89 [0.80-29.72]	3.21 [0.45-22.8]
No	95	310	1	1
Wealth index
Poorest	58	133	2.04 [1.04-4.01]	1.02 [0.43-2.43]
Middle	23	105	1.02 [0.48-2.17]	0.68 [0.23-1.54]
Richer	4	13	1.44 [0.40-5.14]	0.58 [0.12-2.81]
Richest	13	61	1	1

Abbreviation: COR: crude odds ratio.

Discussion

This study aimed to assess the prevalence of undernutrition and its associated factors. The findings revealed that the prevalence of undernutrition was 23.9% (95% CI [20.00-28.28%]). This result is comparable to the findings from studies conducted in Arba Minch, Ethiopia (23.72%), Nekemte, Ethiopia (24%), and Senegal (19.2%).^12,32,33

However, the prevalence of undernutrition was low as compared to the study reports from other developing countries such as Botswana (28.5%) China (37.2%), Brazil (43%) and Nigeria (43.3%).^34–37The observed discrepancy could be attributed to the clinical stage of the study participants, where majority of them found at the clinical stage one in the current study compared to the study from Brazil.³⁴ Obviously, late clinical stage of HIV increases the odds of developing undernutrition, mainly through higher nutritional requirement coupled with poor food intake, and malabsorption of nutrients. Moreover, the higher prevalence of undernutrition in the later study settings could be related to sample size difference,^35,37 absence of important care components, including routine nutritional screening in Botswana,³⁵ and variations in nutritional status measurements and the study design in Nigeria.³⁶

Furthermore, the finding of the study indicated the prevalence of undernutrition obtained from our study was higher than the study conducted South Africa, which is 13%,³⁸ Singapore 16%,³⁹ and Tanzania 18.4%.⁴⁰ The discrepancy in the prevalence of undernutrition might be due to difference in the study design, socioeconomic status, residence, culture and feeding styles of different ethnic groups, clinical stages of HIV, current CD4 cell count, health care awareness of the respondents, and the difference in ART care services like routine nutritional screening and variations in measurements of nutritional status.

The observed differences in undernutrition prevalence between countries may be influenced by factors such as ART availability, healthcare infrastructure, local dietary practices, and socioeconomic conditions. Variations in dietary diversity and food security have been reported across different regions and study populations, reflecting differences in food access and economic status that can affect nutritional outcomes among PLHIV.⁴¹ In resource-limited settings, the high burden of HIV places additional strain on healthcare systems and may limit the availability of comprehensive nutritional support alongside ART, potentially leading to higher rates of undernutrition compared with settings with stronger health infrastructure and integrated care services.^42,43

After controlling possible confounding effects of other covariates, patients who had poor adherence were 4 times more likely to develop undernutrition as compared to those who had good adherence. This finding was supported by study done in Senegal.³²This may be due to poor ART adherence leads to viral replication, destruction of CD4 cells, compromised immunity, and advanced disease progression; finally leads to reducing the dietary intake and nutrient absorption, finally leads for undernutrition.⁴⁴

Patients taking ART for less than 24 months are 9.20 times more likely to develop undernutrition as compared to those who are taking more than 24 months. This report was consistent with study conducted in Arba Minch and study conducted in West Shewa Zone.^12,45 This association may be due to the action of ART drugs reducing viral load by increasing CD4 number and giving recovery for the patient through time to time and ARV drug improvement of immune status of the patient against opportunistic infection promoting healthy life.

Patients who had opportunistic infections were 2.35 times more likely to develop undernutrition as compared to those who do not have opportunistic infections. It is consistent when compared to the study conducted in Debre Markos and in Asella, Ethiopia.⁴⁶ This strong association might be due to opportunistic reducing eating pattern (anorexia), difficulty swallowing or painful swallowing, malabsorption and diarrhea, altered metabolism of nutrients, increased utilization of nutrients, and greater loss of nutrients and complications of opportunistic infections like diarrhea could worsen patients’ nutritional status.⁴⁷

As food security scale is concerned, those severely food insecure and moderately food insecure were 2.53 times and 2.17 more likely undernourished as compared to food secured respectively. This finding is consistent with studies done in southern region and Zimbabwe, Ethiopia.^48,49 Evidences showed that HIV/AIDS deepens food insecurity and affects the nutritional status of PLWHA leading to weight loss and wasting since PLWHA may no longer hold jobs, manufacture goods, and provide services or because of the decrease in productivity. These findings indicated that the negative interactive effects of undernutrition, inadequate food consumption, and HIV infection demand multisector interventions.^32,50

Patients with low dietary diversity scores were more than twice as likely to experience undernutrition compared to those who had higher dietary diversity scores. This finding is consistent with evidence from study conducted in Ethiopia.⁵¹ Dietary diversity plays a critical role in meeting energy and essential nutrient requirements, particularly among populations vulnerable to nutrient deficiencies. Insufficient variety in the diet, coupled with increased nutritional demands, has been associated with a heightened risk of adverse nutritional and developmental outcomes, which tend to become more pronounced over time.⁵²

Although ART-related side effects were not statistically significantly associated with undernutrition in this study, clinical evidence suggests that gastrointestinal symptoms such as nausea, vomiting, and diarrhea can reduce dietary intake and contribute to poor nutritional outcomes among PLHIV. Loss of appetite and eating difficulties due to drug side effects have been linked to malnutrition in other HIV cohorts. Additionally, WHO nutrition care guidelines recognize that ART side effects may diminish food intake and complicate nutritional management among ART users.⁵³

Limitations

Recall bias was a limitation of this study, particularly in the assessment of household food insecurity and household assets, as these measures relied on participants’ self-reported information. Additionally, the use of anthropometric measurement (BMI) to assess nutritional status does not capture body fat distribution, which may limit the interpretation of nutritional status among participants. Future studies should consider longitudinal or cohort study designs to better establish temporal relationships and reduce recall bias. Moreover, incorporating more comprehensive nutritional assessment methods, such as body composition analysis or waist-to-hip ratio measurements, is recommended to better assess fat distribution.

Conclusion and Recommendations

The prevalence of undernutrition among adults receiving second-line ART was high. Poor treatment adherence, opportunistic infections, shorter duration of therapy, household food insecurity, and low dietary diversity were significantly associated with undernutrition. Strengthening nutritional counseling, promoting dietary diversification, linking food-insecure households to food support and social protection programs, and integrating routine nutritional assessment and support into HIV care are recommended to improve nutritional outcomes in this population. Healthcare providers should early monitor, evaluation, and treat patients with the opportunistic infection before threatening and complication. Health workers provide health education daily for improve the food intake of patients. The government should prepare and implement appropriate strategies to improve economic status for alleviating the problem of household food insecurity. The nongovernment organization should support patients with severe household food insecurity by food aid. It is better if investigators conducted a study by using a different method of body composition measurement not only by BMI.

Supplemental Material

sj-docx-1-jia-10.1177_23259582261432458 - Supplemental material for Undernutrition and Associated Factors Among Adults on Second-Line Antiretroviral Therapy in Debark, Ethiopia: A Cross-Sectional Study

Supplemental material, sj-docx-1-jia-10.1177_23259582261432458 for Undernutrition and Associated Factors Among Adults on Second-Line Antiretroviral Therapy in Debark, Ethiopia: A Cross-Sectional Study by Worku Chekol Tassew, Agerie Mengistie Zeleke, Yeshiwas Ayale Ferede, Adane Nigusie Weldeab and Girum Meseret Ayenew in Journal of the International Association of Providers of AIDS Care (JIAPAC)

Supplemental Material

sj-docx-2-jia-10.1177_23259582261432458 - Supplemental material for Undernutrition and Associated Factors Among Adults on Second-Line Antiretroviral Therapy in Debark, Ethiopia: A Cross-Sectional Study

Supplemental material, sj-docx-2-jia-10.1177_23259582261432458 for Undernutrition and Associated Factors Among Adults on Second-Line Antiretroviral Therapy in Debark, Ethiopia: A Cross-Sectional Study by Worku Chekol Tassew, Agerie Mengistie Zeleke, Yeshiwas Ayale Ferede, Adane Nigusie Weldeab and Girum Meseret Ayenew in Journal of the International Association of Providers of AIDS Care (JIAPAC)

Footnotes

Acknowledgments

We would like to thank Debark University, School of Health Science for providing this golden opportunity to practice my research skill and data collectors for their support.

ORCID iDs

Worku Chekol Tassew

Agerie Mengistie Zeleke

Yeshiwas Ayale Ferede

Ethics Approval,Confidentiality,and Informed Consent

Ethical clearance was obtained from the Institutional Review Board of Debark University, College of Health Sciences (Reference No. DUHS/25071/2025). Given the sensitive and stigmatized nature of HIV-related information, strict measures were implemented to ensure confidentiality and protect participants’ personal and health-related data. Personal identifiers were excluded from all data collection tools, and access to study records was restricted to the principal investigator and supervisors only. All documents were securely stored in a locked cabinet to prevent unauthorized access.

Written and verbal informed consent was obtained from all participants after providing a clear explanation of the study objectives, procedures, potential risks, and benefits. Participants were informed of their right to decline participation or withdraw from the study at any time without any consequences. These ethical safeguards were implemented to uphold participants’ privacy, maintain trust, and ensure compliance with national and international ethical guidelines for HIV-related research.

Authors’ Contributions

WCT: conceptualization, formal analysis, resource, supervision, investigation, methodology, visualization, writing—original draft, and writing—review and editing; YAF, ANW, GMA, and AMZ: writing—original draft, and writing—review and editing.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Availability of Data and Materials

All relevant data are within the manuscript and its supporting information files.

Clinical Trial Number

Not applicable.

Supplemental Material

Supplemental material for this article is available online.

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