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  • Research article
  • Open Access
  • Open Peer Review

Prevalence of malnutrition and its associated factors among adult people living with HIV/AIDS receiving anti-retroviral therapy at Butajira Hospital, southern Ethiopia

BMC Nutrition20151:5

https://doi.org/10.1186/2055-0928-1-5

©  Gedle et al.; licensee BioMed Central. 2015

  • Received: 15 July 2014
  • Accepted: 11 December 2014
  • Published:
Open Peer Review reports

Abstract

Background

Malnutrition and human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) are highly prevalent in Sub-Saharan Africa, and they are linked in a vicious cycle. Intestinal parasite co-infection worsens the effect of malnutrition among HIV patients. However, the magnitude of malnutrition and its determinant factors among people living with HIV/AIDS are not well understood in Butajira in particular and Ethiopia in general. The aim of this study was to determine the prevalence of malnutrition and its associated factors among adult people living with HIV/AIDS and receiving anti-retroviral therapy (ART).

Methods

Institution-based cross-sectional study was conducted, and systematic random sampling technique was used to select study subjects. A total of 305 study subjects were enrolled in the study. Structured and pre-tested questionnaire was used to collect demographic data. From each sampled patient, anthropometric and laboratory data were also collected. Both bivariate and multivariate logistic regression analyses were used to assess the effect of the various factors on the level of malnutrition. A P value ≤0.05 at 95% CI was considered statistically significant.

Results

The overall prevalence of malnutrition was 25.2% of which 49, 19, and 9 patients were mildly, moderately, and severely malnourished, respectively. Multivariate logistic regression analysis revealed that living in rural area, anemia, and intestinal parasitic co-infection were significantly associated with malnutrition (AOR = 1.98, 1.9, 2.85, respectively).

Conclusions

The prevalence of malnutrition among HIV/AIDS patients receiving ART in Butajira was high and intestinal parasite co-infection was found as an important risk factor associated with malnutrition.

Keywords

  • Malnutrition
  • HIV/AIDS
  • ART
  • Intestinal parasites

Background

Globally, more than 800 million people are chronically undernourished [1], and over 35 million people are living with human immunodeficiency virus (HIV). Although new cases have been reported all over the globe, the majority of cases have been reported in low- and middle-income countries, particularly in Sub-Saharan Africa (SSA) [2]. In Ethiopia, 1.5% of adult people aged 15–49 are infected with HIV [3]. Malnutrition combined with human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) brought significant crisis in SSA in particular and globally in general. HIV affects the health status of an individual, and it has an impact on households, communities, and economic growth of the nations. In most developing countries, malnutrition together with infectious diseases aggravated the HIV/AIDS pandemic and contributed for both mortality and morbidity of patients [4, 5]. HIV/AIDS and malnutrition effects are interconnected, worsen one another in a vicious cycle, and cause progressive damage to the immune system independently. HIV specifically affects nutritional status by reducing food intake, increasing energy requirements, and harmfully affects nutrient absorption and metabolism [6, 7]. The effects of malnutrition by itself can decrease cluster of differentiation-four (CD4+) T cells and contribute to abnormal B-cell responses [8, 9] which adversely affect the overall clinical outcome and exacerbate HIV-related immune depression [10].

Anti-retroviral therapy (ART) medications can cause nausea, vomiting, loss of appetite, diarrhea, and other disorders [11]. Diarrhea adversely affects the nutritional status of people living with HIV/AIDS (PLWHA) [12, 13]. Commonly identified metabolic complications in adults living with HIV/AIDS who received ART include lipodystrophy, insulin resistance, dyslipidemia, lactic acidosis, and osteopenia [14, 15].

Adequate nutrition is necessary to manage opportunistic infections, maintain the immune system, optimize response to medical treatment, and support optimal quality of life for PLWHA [16]. Evidence has shown that good nutrition may contribute to slowing the progression of the disease. Nutrition interventions can also help to optimize the benefits of antiretroviral drugs and may increase compliance with treatment regimens [17].

The prevalence of malnutrition among PLWHA was reported higher in different parts of the world. In Ethiopia, malnutrition among PLWHA receiving ART has been a major challenge to accomplish the full impact of intervention. There are different reports that showed large magnitude of both HIV/AIDS and malnutrition in Ethiopia. However, the burden of malnutrition among PLWHA and receiving ART is not fully understood in Butajira Zonal administration in particular and in the nation in general. Moreover, determinants of nutritional status especially intestinal parasitic infection are not comprehensively studied. Hence, this study was designed to assess the prevalence of malnutrition and its associated factors among adult HIV/AIDS clients receiving ART at Butajira Hospital, Southern Ethiopia.

Methods

Study area, design, and period

The study was conducted at Butajira Hospital which is found in Butajira town, Gurage Zone, Southern Nations Nationalities and People’s Region (SNNPR), located 135 km from the capital city, Addis Ababa, Ethiopia. The town lies on the average at 2,100 m above sea level. Butajira Hospital is a zonal hospital with 110 beds that gives health services for people living in Butajira and the surrounding rural kebeles. The study was an institution-based cross-sectional study conducted from October 2013 to June 2014.

Populations

The source populations were all adult PLWHA in Butajira town and the surrounding area that were enrolled for ART follow-up service at Butajira Hospital. The study populations were people with the age of 18 years and above who were currently receiving ART. Patients who were receiving ART and involved in ART follow-up clinic at Butajira Hospital and aged 18 years and above were included in the study. However, pregnant women, lactating mothers (6 months of postpartum), and seriously ill and/or patients with spinal deformity were excluded.

Operational definition

Drug adherence status: it was estimated by percent of missed dose enclosed in the last 6 month follow-up time from patient ART follow-up form combined with self-reported adherence measurement technique by asking the patients about the number of times they have missed taking their pills each month and recorded. The category was based on WHO classification.

Good adherence: there is good adherence if the average adherence is greater than 95% (he/she missed ≤2 doses of 30 doses or ≤3 doses of 60 doses).

Fair adherence: there is fair adherence if the average adherence is 85%–94% (he/she missed 3–5 doses of 30 doses or 3–9 doses of 60 doses).

Poor adherence: there is poor adherence if the average adherence is <85% (he/she missed ≥6 doses from 30 doses or >9 doses of 60 doses).

Sample size and sampling technique

The sample size was determined using single population proportion formula taking 22.1% [18] prevalence of malnutrition among adults with HIV/AIDS on ART with 5% marginal error and 95% confidence interval (CI) of certainty (alpha = 0.05). In this study, 15% of non-response rate was taken, and the final sample size was determined as 305. A systematic random sampling technique was used to select the study subjects. According to the hospital report, on average, 10–20 patients that were currently taking ART have been visiting the hospital daily. Considering 3 months of study period, 660 patients were expected to visit the hospital. Since the sample size was determined as 305, the sampling interval was determined as 2. Of the first two subjects, one patient was randomly selected by lottery method; and then every second patient was selected to participate in the study.

Socio-demographic data

The data was collected from March to May 2014 using structured questionnaire. Socio-demographic characteristics were focused on data such as age, sex, monthly income, and educational and marital status together with nutrition and clinical-related characteristics were collected. Four data collectors (one nurse, one health officer, and two laboratory technicians) were recruited, and 2 days of training were given. The data collection process was followed daily by the principal investigator.

Laboratory data

Data on opportunistic disease in the past 6 months, WHO clinical stages of disease, drug adherence, and chronic diseases were obtained from patient charts and ART follow-up forms. CD4+ T cell count was measured with BD FACS machine (US) and categorized according to its clinical significance. Hemoglobin was measured with Cell Dyne hematology analyzer (US). Hemoglobin level ranged between 13–17 and 12–16 g/dl was considered as normal for male and female patients, respectively. Patients were graded anemic when the hemoglobin concentration was <12 and <13 g/dl for male and female patients, respectively.

Anthropometric data

Anthropometric measurements (weight, height) were recorded by a trained nurse. Weight of the participants was measured in kilograms with 0.1 kg increments using standard beam balance, and the scale was checked at zero before and after each measurement. Each participant was asked to remove heavy clothes. Measurement of height was conducted using the standard measuring scale and recorded to the nearest 0.5 cm. The participants were asked to take off their shoes, stand erect, and look straight in vertical plain.

Stool sample collection and microscopy

About 2 g of stool samples were collected in a clean leak-proof cupped plastic container following standard operating procedures. Each sample was examined by two clinical laboratory technicians independently for intestinal parasites using direct microscopic and concentration methods at Butajira Hospital parasitology laboratory. In the case of direct microscopic examination, stool samples were mixed with physiological saline (0.85% NaCl) on a microscope slide, covered with a cover slip, and then examined microscopically using low power objective first and high dry power objective to examine cysts of intestinal parasites. In the case of formal-ether concentration method, about 2 g or 2 ml of stool sample was mixed with 10 ml of normal saline solution and thoroughly mixed. This was filtered through two layers of gauze into a centrifuge test tube and centrifuged for 1 min at a speed of approximately 25,000 rpm for 10 min. When the supernatant fluid was very cloudy, the deposit was washed again by mixing it with 10 ml of normal saline. After pouring or removing the supernatant fluid, 10 ml of formaldehyde solution (10% formalin solution) was added to the sediment. After mixing the suspension well and allowed to stand for 5 min, 3 ml of ether was added and was immediately stopped and vigorously shacked for 30 s. The preparation was centrifuged for 1 min at low speed, usually 1,500 rpm. There appeared four layers in the preparation; the first layer which is an ether, the second layer which is a debris, the third layer which is a formaldehyde solution, and the fourth layer which is the deposit containing stages of parasites (cysts, egg, and/or larvae). The supernatant was removed by tilting the tube and poured off all the fluid. The sediment was mixed with the remaining small fluid, and about two drops of the deposit was placed on a slide, to which a drop of iodine solution was added and covered with a cover slide. The entire preparation was examined using × 10 objective for protozoa eggs and × 40 objective for cysts.

Quality control

The questionnaire was adapted and modified into our context from previous literatures. It was prepared first in English, translated into the local language Amharic, and then retranslated back to English by an expert to maintain its consistency. Training was given for data collectors and supervisor. Pre-testing of the questionnaire was made on 20 patients receiving ART in the nearby health center 3 weeks prior to the actual survey. Data collection process was strictly followed day to day by the supervisor and principal investigator. Standard operating procedures were followed during sample collection, processing, transportation, and identification of intestinal parasites. Data was checked for completeness, coded, and first entered in to EPI-info version 7; then, it was rechecked and transferred to Statistical Package for Social Science (SPSS) version 20 for analysis. Chi-square was used to carry out descriptive analysis. Bivariate and multivariate logistic regression analyses were used to assess the effect of the various factors on the level of malnutrition and to control possible confounders. The absence of multi-co-linearity was checked by using VIF/tolerance. The model adequacy was checked by using Hosmer and Lemeshow goodness of fit test. P value ≤0.05 at 95% CI was considered statistically significant.

Ethical consideration

Ethical approval was obtained from the ethical review committee of the School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, prior to data collection. Permission was taken from Butajira Zonal Hospital administrators. Written informed consent was obtained from each individual after the purpose of the study was explained. Participants were told that they had full right to participate or not, and they were also informed that all the data obtained from them would be kept confidential using codes instead of any personal identifiers. Any study participants who were positive for intestinal parasite were referred to ART clinicians for treatment. Finally, those participants identified as undernutrition were given nutritional counseling and RUTF in collaboration with the clinicians working in ART clinic at Butajira Hospital.

Results

Socio-demographic characteristics of the study participants

A total of 305 adult PLWHA receiving ART were involved in this study. The majority of participants (60.7%) were in the age group 30–44 years with the mean and standard deviation (±SD) of 39.5 (±9.9) years. Sixty-two percent of study participants were women, and more than half (50.5%) of the study participants were currently married. The majority of participants (86.6%) have low monthly income (<1,000 Ethiopian birr (ETB) as shown in (Table 1).
Table 1

Socio-demographic characteristics of the study participants

Characteristics

 

Frequency (n)

Percent (%)

Sex

Male

116

38.0

Female

189

62.0

Age

18–29

36

11.8

30–44

185

60.7

≥45

84

27.5

Marital status

Single

19

6.2

Married

154

50.5

Divorced

42

13.8

Widowed

81

26.6

Separated

9

3.0

Family size

≤3

148

22.8

4–6

137

21.1

>6

20

3.1

Educational status

Unable to read and write

121

39.7

Able to read and write

38

12.5

Primary education

80

26.2

Secondary education

47

15.4

Tertiary education

19

6.2

Religion

Orthodox

143

46.9

Muslim

102

33.4

Protestant and Catholic

60

19.7

Ethnicity

Gurage

178

58.4

Silitie

55

18.0

Amhara

40

13.1

Oromo

14

4.6

Hadiya

18

5.9

Occupation

Governmental employer

40

13.1

Self employer

51

16.7

Farmer

39

12.8

Merchant

45

14.8

Daily laborer

60

19.7

House wife

49

16.1

Jobless

21

6.9

Residence

Urban

177

58.0

Rural

128

42.0

Monthly income in ETB

<1,000

264

86.6

 

≥1,000

41

13.4

More than half of the patients were married, many had a family size of 4–6 members, and many were unable to read and write. The majority of the patients had less than 1,000 Ethiopian birr monthly income.

Clinical profiles and ART status of the study participants

The HIV status of patients showed that 60.3% (n = 184) were at WHO clinical stage I. One hundred twenty-seven patients (41.6%) had current or past history of opportunistic infections, of which 73 patients (23.9%) had tuberculosis infection and accounted for the uppermost co-infection. The median CD4+ T cell count and mean hemoglobin concentration level of participants were 400 cells/μl with inter-quartile range (329 IQR) and 13.0 g/dl with SD ±1.7, respectively (Table 2). One hundred thirty-two patients (43.3%) were on ART treatment regimen 1e (TDF + 3TC + NVP), and another 122 (40%) were on 1c (AZT + 3TC + NVP). However, quite a number of patients (38.7%) had changed the ART regimen due to toxicity/side effects during follow-up period (Table 2).
Table 2

Clinical profiles and ART status

Variables

  

Frequency (n)

Percent (%)

Eating difficulty

No

 

235

77.0

Yes

Problems

70

23.0

 

Loss of appetite

63

20.7

 

Vomiting

20

6.6

 

Nausea

13

4.3

 

Swallowing difficulty

6

2

Gastrointestinal symptoms

No

 

255

83.6

Yes

Problems

50

16.4

 

Diarrhea

28

9.2

 

Indigestion

22

7.2

 

Constipation

7

2.7

WHO clinical stage

Stage I

 

184

60.3

Stage II

 

54

17.7

Stage III

 

60

19.7

Stage IV

 

7

2.3

CD4+ T cell count

<200 cells/μl

 

51

16.7

200–350 cells/μl

 

73

23.9

351–500 cells/μl

 

76

24.9

>500 cells/μl

 

105

34.4

Anemia status

Normal

 

220

72.1

Anemic

 

85

27.9

Current/past OI in the past 6 months

No

 

178

58.4

Yes

Problems

127

41.6

 

Acute/chronic diarrhea

45

14.8

 

Tuberculosis

73

23.9

 

Oral thrush

17

5.6

 

Oral ulcer

8

2.6

 

Pneumonia

8

2.6

 

Zoster

3

1.0

 

Pneumocystis carinii

1

0.3

ART regimens

1a (d4T + 3TC + NVP)

 

7

2.3

1c (AZT + 3TC + NVP)

 

122

40.0

1d (AZT + 3TC + EFV)

 

14

4.6

1e (TDF + 3TC + EFV)

 

132

43.3

1f (TDF + 3TC + NVP)

 

26

8.5

2b (TDF + 3TC + LPV/r)

 

4

1.3

Duration of ART

<6 months

 

38

12.5

6–12 months

 

47

15.4

1–3 years

 

53

17.4

>3 years

 

167

54.8

Regimen change

No

 

187

61.3

Yes

 

118

38.7

Reasons for change

Toxicity/side effect

 

117

38.4

New tuberculosis

 

1

0.3

Drug adherence

Good

 

277

90.8

Fair

 

20

6.6

 

Poor

 

8

2.6

Many patients were on stage I HIV status, one-third had CD4+ T cell count less than 500 cells/μl, and more than half of the patients had a history of opportunistic infection. Many of the patients took ART treatment for more than 3 years but had toxicity/side effect. However, drug adherences for many of the patients were good enough.

AZT zidovudine, d4T stavudine, EFV efavirenz, NVP nevirapine, TDF tenofovir, 3TC lamivudine, LPV/r lopinavir + ritonavir.

Nutrition-related characteristics of the study participants

Data on the household food insecurity and dietary diversity status showed that 79% of participants were food insecure, of which 14 (4.6%), 99 (32.5%), and 128 (42%) were mildly, moderately, and severely food insecure, respectively. The mean household dietary diversity was 4.93 with SD ±1.8. Moreover, 121 (39.7%) participants were with inadequate dietary diversity (Table 3).
Table 3

Nutrition-related characteristics

Variables

 

Frequency (n)

Percent (%)

Change of feeding style after knowing HIV status

No

227

74.4

Yes

75

24.6

Type of change of feeding style

Frequency

18

5.9

Quality of food

75

24.6

Quantity

3

1.0

Dietary counseling

No

143

46.9

Yes

162

53.1

Organizational support other than medication

No

263

86.2

Economical support

7

2.3

RUTF

26

8.5

Economical and RUTF

9

3.0

Household food insecurity status

Food secure

64

21.0

Mildly food insecure

14

4.6

Moderately food insecure

99

32.5

Severely food insecure

128

42.0

Household dietary diversity

Inadequate

121

39.7

 

Adequate

184

60.3

Nearly half of the patients had no any type of dietary counseling, and many were severely food insecure.

Intestinal parasite infection among the study participants

In this study, 26.6% of the study participants were co-infected with one or more intestinal parasites and six different types of intestinal parasitic species were identified. The prevalence of Entamoeba histolytica/dispar was 11.5% (n = 35) and that of Taenia species 7.2% (n = 22) followed by Giardia lamblia 5.3% (n = 16) (Table 4).
Table 4

Intestinal parasite co-infection

Intestinal parasites

Frequency (n)

Percent (%)

Negative

 

224

73.4

Positive

 

81

26.6

Protozoa’s

Entamoeba histolytica/dispar trophozoite

22

7.2

Entamoeba histolytica/dispar cyst

13

4.3

Giardia lamblia trophozoite

14

4.6

Giardia lamblia cyst

2

0.7

Helminthes

Tanea species

22

7.2

Ascaris lumbricoides

9

3.0

Strongyloid stercoralis

5

1.6

Hookworm species

2

0.7

Multiple parasitic infections

Entamoeba histolytica/dispar trophozoite + Giardia lamblia trophozoite

2

0.7

Entamoeba histolytica/dispar trophozoite + Ascaris lumbricoides

2

0.7

 

Giardia lamblia trophozoite + Tanea species

1

0.3

The prevalence of intestinal parasitic infection was 26.6%. Entamoeba histolytica/dispar trophozoite and Tanea species were the dominant intestinal parasites identified.

Prevalence of malnutrition

The overall prevalence of malnutrition (BMI <18.5 kg/m2) among PLWHA receiving ART at Butajira Hospital was 25.2% (95% CI: 20.0%–30.2%). Mild, moderate, and severe malnutrition were observed on 49 (16.1%), 19 (6.2%), and 9 (3.0%) participants, respectively. The mean BMI for male and female was 20.77 (SD ± 3.15) and 21.04 (SD ± 3.56), respectively. The prevalence of malnutrition among male patients was 25.9% (95% CI: 18.3%–34.3%) but 24.9% (95% CI: 18.8%–31.2%) among females. The prevalence of malnutrition was also different by the age of the study subjects. Among 77 (25.2%) malnourished subjects, the age group 30–44 were mostly affected, 42 (13.8%), followed by the age group above 44 years, 29 (9.5%).

Factors affecting malnutrition

In this study, both bivariate and multivariate logistic regression analysis were computed. Out of 11 selected variables that showed significant association with malnutrition in the bivariate model, only five variables (residence, eating difficulty, ready-to-use therapeutic food (RUTF), anemia, and intestinal parasitic infection) were significantly associated with malnutrition when data were computed with multivariate logistic regression analysis. Six variables that showed association on the bivariate model (age, educational status, gastrointestinal symptoms, diarrhea, Household Food Insecurity Access Scale (HFIS), and Household Dietary Diversity (HDD) were not statistically associated with malnutrition in the multivariate model (Table 5). In addition, being rural area dweller was significantly associated with malnutrition (P = 0.02). Patients living in rural area were two times more likely to be malnourished as compared to those living in urban areas (AOR = 1.98; 95% CI: 1.10, 3.53). Eating difficulty was also positively associated with malnutrition (P = 0.002). Participants who had one or more eating difficulty were 2.69 times more likely to be malnourished as compared to those who were free of eating difficulty (AOR = 2.69; 95% CI: 1.41, 5.11). Ready-to-use therapeutic food (RUTF) was negatively associated with malnutrition. Individuals who were not taking RUTF were 82% times less likely to be malnourished than those who were taking RUTF (AOR = 0.18; 95% CI: 0.08, 0.40). Anemia was also positively associated with malnutrition (P = 0.03). Participants who were anemic were 1.94 more likely to be malnourished than those with normal hemoglobin level (AOR = 1.94; 95% CI: 1.05, 3.57). Intestinal parasitic co-infection was also significantly associated with malnutrition. (P = 0.001). Participants who had one or more intestinal parasites were 2.85 times more likely to be malnourished as compared to those who were free of intestinal parasites (AOR = 2.85; 95% CI: 1.54, 5.27) (Table 5).
Table 5

Factors associated with malnutrition among PLWHA receiving ART

Predictors

Undernutrition

COR (95% CI)

AOR (95% CI)

Pvalues

 

Yes

No

   

Age

 18–29

6

30

1

  

 30–44

42

143

1.47(0.57–3.76)

  

  > 44

29

55

2.64(0.98–7.06)

  

Residence

 Urban

35

142

1

1

 

 Rural

42

86

1.98(1.17–3.34)

1.98(1.10–3.53)

0.02

Educational status

 Unable to read and write

40

81

2.63(0.72–9.57)

  

 Able to read and write

12

26

2.46(0.60–10.08)

  

 Primary education

16

64

1.33(0.35–5.14)

  

 Secondary education

6

41

0.78(0.17–3.50)

  

 Tertiary education

3

16

1

  

Eating difficulty

 Yes

29

41

2.76(1.56–4.88)

2.69(1.41–5.11)

0.002

 No

48

187

1

1

 

Drug adherence

 Yes

18

32

1.87(0.98–3.57)

  

 No

59

196

1

  

Diarrhea

 Yes

12

16

2.45(1.10–5.43)

  

 No

65

212

1

  

RUTF

 Yes

22

13

1

1

 

 No

55

215

0.15(0.07–0.3)

0.18(0.08–0.40)

0.00

Anemia

 Yes

31

54

2.17(1.25–3.76)

1.94(1.05–3.57)

0.03

 No

46

174

1

1

 

HFIS

 Food secure

6

58

1

  

 Mildly food insecure

2

12

1.61(0.29–8.97)

  

 Moderately food insecure

26

73

3.44(1.33–8.92)

  

 Severely food insecure

43

85

4.89(1.95–12.2)

  

HDD

 Inadequate

37

84

1.59(0.94–2.67)

  

 Adequate

40

144

1

  

Intestinal parasite

 Present

33

48

2.81(1.62–4.89)

2.85(1.54–5.27)

0.001

 Absent

44

180

1

1

 

Living in rural area, eating difficulty, RUFF, anemia, and intestinal parasite infection were significantly associated with under nutrition.

Discussion

This study is focused on assessing the prevalence of malnutrition and its associated factors among adult PLWHA and currently receiving ART. The overall prevalence of malnutrition (25.2%) was relatively lower than other reports conducted in different parts of the world (37.2%–43%) [19–21]. The prevalence of malnutrition was also reported different in different parts of Ethiopia. For example, Hailemariam et al. reported a 12.3% prevalence of malnutrition in Dilla, southern parts of Ethiopia [22]. On the other hand, higher prevalence of malnutrition (42.3%) was reported in Tigray, northern parts of Ethiopia [23]. The prevalence of malnutrition in Gondar and Bahirdar, northwestern parts of Ethiopia, was reported 27.8% and 25.5%, respectively [18, 24].The discrepancy of malnutrition among different parts of the country may reflect the existence of different socio-economic and other factors that are practiced by these different communities probably as a result of different ethnic experiences. The high prevalence of malnutrition reported in Tigray was only on women patients. This may indicate gender-dependent prevalence of malnutrition among HIV-positive women. There are also reports that support women are biologically, socially, and economically more vulnerable to both HIV/AIDS and malnutrition [25, 26]. Women have lower muscle mass and greater amount of total body fat than men with an equivalent BMI, which may increase the prevalence of malnutrition, since sex and muscle mass can affect the relationship between BMI and body fat [27].

Patients living in rural area were two times more likely to be malnourished as compared to those living in urban areas. It will not be unwise to expect lower socio-economic status, reduced awareness about nutrition, lower food access and diversity, and narrower availability of health, water, and sanitation services in rural dwellers than people living in urban in the study area as these are commonly observed in third world and developing countries. Eating difficulty was another significantly associated variable with malnutrition among PLWHA receiving ART. Participants who had one or more eating difficulty were 2.69 times more likely to be malnourished as compared to those who were free of eating difficulty. This finding is in accordance with the results of former studies conducted in Gondar and Bahirdar, northwestern Ethiopia [18, 24]. Reduction of food consumption due to loss of appetite, vomiting and nausea due to the side effects of ART drugs, and swallowing difficulty due to oral thrush or ulcer lead to reduced energy intake and may also be the main reasons for the loss of weight among PLWHA [28].

This study found a significant positive association between anemia and malnutrition. Participants who were anemic were 1.94 times more likely to be malnourished than those with normal hemoglobin level. Similar reports were documented in a study conducted in Tigray [23]. This association of anemia with malnutrition might be due to alterations in bone marrow and spleen erythropoiesis, diminution in reticulocyte as a result of protein-energy malnutrition. Haemopoietic tissue has a high rate of regeneration, and cellular proliferation presents a high demand for protein for the process of haemopoiesis. Bone marrow atrophy is common in protein-energy malnutrition, which results from abnormalities of stem cells or defects in stromal cells, which would alter the haemopoietic microenvironment [29].

There was also a significant negative association between RUTF with malnutrition in the current study. Individuals who were not taking RUTF were 82% times less likely to be malnourished than those who were taking RUTF, and this was also in accordance with previous reports [23]. However, the current result on the association of RUTF with malnutrition contradicts with a report from other countries such as Central Haiti [30] and Uganda [31]. A number of reasons can contribute for the difference including the study design. The former studies conducted in Central Haiti were prospective cohort study, which have enough time to observe the potential effect of RUTF on that of malnutrition. On the other hand, the participants of the current study may not take RUTF properly due to sharing to their family members, selling to get money, and they may not respond to RUTF due to recurrent opportunistic infections, clinical stages of disease, and others.

The other pertinent finding of the current study was a highly significant positive association of intestinal parasites with malnutrition. Participants who had one or more intestinal parasites were 2.85 times more likely to be malnourished as compared to those who were free of intestinal parasites. This positive association might be due to nutrient demand of parasite itself, frequent episode of diarrhea and reduced appetite, blocking of the absorbing surface of the mucosa by adult worms, and altered absorption of nutrients [32, 33]. Many of the populations at high risk for HIV also live in highly endemic areas of intestinal parasitic infections, which are mainly acquired in childhood and remain as chronic infections into adulthood [34]. Several investigators reported lower levels of hemoglobin as a result of pathogenic intestinal parasitic infections [35]. Entamoeba histolytica leads to necrosis of intestinal mucosa and bleeding; Giardia lamblia to malabsorption; and Tricuris is suggested to associate with anemia mediating through iron deficiency caused by blood loss [36]. Infection by hookworm causes iron deficiency anemia, and Ascaris lumbricoides is known to influence nutritional status; but its impacts on anemia are less clear [37].

The limitation of the current study could be the study design as cross-sectional study design by its nature limits information about cause and effect relationship in the majority of predictors. Recall bias and social desirability bias were the limitations of the study when measuring adherence to HAART and duration of HART. Moreover, only anthropometric measurement (BMI) was used to assess the nutritional status of participants, which assess mainly the public health burden of malnutrition. The study did not add some laboratory methods used to assess nutritional status like micronutrient deficiencies.

Conclusions

This study revealed that malnutrition is high among PLWHA receiving ART in Butajira Hospital, southern Ethiopia. Living in rural area, eating difficulty, anemia, RUTF, and intestinal parasite co-infection were the most significant factors affecting malnutrition. Strengthening household food security status of patients besides nutritional support and ART treatment, consistent detection of intestinal parasites and prompt treatment or de-worming, and regular checkup of hemoglobin concentration among PLWHA in general and those taking ART in particular is recommended.

Declarations

Acknowledgements

We would like to thank the Butajira Hospital ART and laboratory staffs for all the help and support given for us during the data collection and laboratory investigation. We also thank Mr. Zenebe Gedle, Mr. Dargaze Kibru, Mr. Yantenew Gedle, and Mr. Getnet Mekuriya for their immense advice and help in collecting the data and in investigating the laboratory samples.

Authors’ Affiliations

(1)
School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences (CMHS), University of Gondar (UOG), Gondar, Ethiopia
(2)
Department of Medical Microbiology, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
(3)
Institute of Public Health, CMHS, UOG, Gondar, Ethiopia

References

  1. Ivers LC, Cullen KA, Freedberg KA, Block S, Coates J, Webb P, et al.: HIV/AIDS, undernutrition, and food insecurity.Clin Infect Dis 2009,49(7):1096–102. 10.1086/605573View ArticlePubMedPubMed CentralGoogle Scholar
  2. UNAIDS: Global Report 2012: UNAIDS Report on the Global AIDS Epidemic. 2013. [ebookpartnership.com]Google Scholar
  3. CSA: Ethiopia demographic and health survey. Addis Ababa: Central Statistical Agency and ICF International USAID; 2011.Google Scholar
  4. Anabwani G, Navario P: Nutrition and HIV/AIDS in sub-Saharan Africa: an overview.Nutrition 2005,21(1):96–9. 10.1016/j.nut.2004.09.013View ArticlePubMedGoogle Scholar
  5. Garcia-Prats AJ, McMeans AR, Ferry GD, Klish WJ: Nutrition and HIV/AIDS.HIV Curriculum 2010, 286:4–5.Google Scholar
  6. WHO: Nutrient requirements for people living with HIV/AIDS: report of a technical consultation. Geneva: World Health Organization; 2003.Google Scholar
  7. Piwoz E, Coursen-Neff Z, Penn A, Brooks L, Vann B, Beatty M, et al.: Nutrition and HIV/AIDS: evidence gaps and priority actions.AWHONN Lifelines 2004,8(4):295–6.View ArticleGoogle Scholar
  8. Gorbach SL, Knox TA, Roubenoff R: Interactions between nutrition and infection with human immunodeficiency virus.Nutr Rev 1993,51(8):226–34.View ArticlePubMedGoogle Scholar
  9. Scrimshaw NS, SanGiovanni JP: Synergism of nutrition, infection, and immunity: an overview.Am J Clin Nutr 1997,66(2):464S-77.PubMedGoogle Scholar
  10. Byron E, Gillespie S, Nangami M: Integrating nutrition security with treatment of people living with HIV: lessons being learned in Kenya.IFPRI 2008,29(2):87–97.Google Scholar
  11. CATIE: A practical guide to HIV drug side effects for people living with HIV.Canada’s source for HIV and hepatitis C: Canada 1st edition. 2002.Google Scholar
  12. Forrest G: Gastrointestinal infections in immunocompromised hosts.Curr Opin Gastroenterol 2004,20(1):16–21. 10.1097/00001574-200401000-00005View ArticlePubMedGoogle Scholar
  13. Guerrant RL, Schorling JB, McAuliffe JF, De Souza MA: Diarrhea as a cause and an effect of malnutrition: diarrhea prevents catch-up growth and malnutrition increases diarrhea frequency and duration.AmJTrop Med Hyg 1992,47(1 Pt 2):28–35.View ArticleGoogle Scholar
  14. Kim RJ, Rutstein RM: Impact of antiretroviral therapy on growth, body composition and metabolism in pediatric HIV patients.Pediatr Drugs 2010,12(3):187–99. 10.2165/11532520-000000000-00000View ArticleGoogle Scholar
  15. Barbaro G: Highly active antiretroviral therapy-associated metabolic syndrome: pathogenesis and cardiovascular risk.Am J Ther 2006,13(3):248–60. 10.1097/01.mjt.0000162013.66614.16View ArticlePubMedGoogle Scholar
  16. Castleman T, Seumo-Fosso E, Cogill B: Food and nutrition implications of antiretroviral therapy in resource limited settings. Washington, DC: Fanta Project; 2003.Google Scholar
  17. Bank W: HIV/AIDS, nutrition, and food security: what we can do. .: World Bank; 2013.Google Scholar
  18. Daniel M, Mazengia F, Birhanu D: Nutritional status and associated factors among adult HIV/AIDS clients in Felege Hiwot Referral Hospital, Bahirdar, Ethiopia.Science 2013,1(1):24–31.Google Scholar
  19. Andrade CS, Jesus RP, Andrade TB, Oliveira NS, Nabity SA, Ribeiro GS: Prevalence and characteristics associated with malnutrition at hospitalization among patients with acquired immunodeficiency syndrome in Brazil.PLoS One 2012,7(11):e48717. 10.1371/journal.pone.0048717View ArticlePubMedPubMed CentralGoogle Scholar
  20. Hu W, Jiang H, Chen W, He SH, Deng B, Wang WY, et al.: Malnutrition in hospitalized people living with HIV/AIDS: evidence from a cross-sectional study from Chengdu, China.Asia Pac J Clin Nutr 2011,20(4):544–50.PubMedGoogle Scholar
  21. Sanon DA GN, Ann AC, Sow PS: Prevalence of malnutrition in a sample of people living with HIV-AIDS (PLWHA) with or without ART and to identify the risk factors associated with malnutrition. Geneva, Switzerland: Int AIDS Conf. 2006. XVI: Abstract no. MOPE0729Google Scholar
  22. Hailemariam S, Bune GT, Ayele HT: Malnutrition: prevalence and its associated factors in people living with HIV/AIDS, in Dilla University Referral Hospital.Arch Public Health 2013,71(1):13. 10.1186/0778-7367-71-13View ArticlePubMedPubMed CentralGoogle Scholar
  23. WHO: Physical status: the use and interpretation of anthropometry. In In report of a WHO expert Committee. vol. 854th ed. Edited by series WTR. Geneva: WHO; 2004.Google Scholar
  24. Hadgu TH, Worku W, Tetemke D, Berhe H: Undernutrition among HIV positive women in Humera Hospital, Tigray, Ethiopia, 2013: antiretroviral therapy alone is not enough, cross sectional study.BMC Public Health 2013,13(1):943. 10.1186/1471-2458-13-943View ArticlePubMedPubMed CentralGoogle Scholar
  25. Friis H: Micronutrients and HIV infection: a review of current evidence, consultation on Nutrition and HIV/AIDS in Africa: Evidence, lessons and recommendations for action. Durban, South Africa: Department of Nutrition for Health and Development World Health Organization; 2005.Google Scholar
  26. Borelli P, Blatt S, Pereira J, Beutler de Maurino B, Tsujita M, Cristina de Souza A, et al.: Reduction of erythroid progenitors in protein–energy malnutrition.Br J Nutr 2007,97(02):307–314. 10.1017/S0007114507172731View ArticlePubMedGoogle Scholar
  27. Louise YC, Gregory JJ, Kenneth AF: Food assistance is associated with improved body mass index, food security and attendance at clinic in an HIV program in central Haiti. a prospective observational cohort study.AIDS Res Ther 2011,7(33):1–8.Google Scholar
  28. Rawat R, Kadiyala S, McNamara PE: The impact of food assistance on weight gain and disease progression among HIV-infected individuals accessing AIDS care and treatment services in Uganda.BMC Public Health 2010,10(1):316. 10.1186/1471-2458-10-316View ArticlePubMedPubMed CentralGoogle Scholar
  29. Jardim-Botelho A, Brooker S, Geiger SM, Fleming F, Souza Lopes AC, Diemert DJ, et al.: Age patterns in undernutrition and helminth infection in a rural area of Brazil: associations with ascariasis and hookworm.Tropical Med Int Health 2008,13(4):458–67. 10.1111/j.1365-3156.2008.02022.xView ArticleGoogle Scholar
  30. Ngzuyen NL, Gelaye B, Aboset N, Kumie A, Williams MA, Berhane Y: Intestinal parasitic infection and nutritional status among school children in Angolela.Ethiopia. J Prev Med Hyg 2012,53(3):157–64.Google Scholar
  31. Infectious disease society of America (IDSA): HIV/TB co-infection: basic facts. The Forum for collaborative HIV research. Virginia, USA: IDSA; 2007.Google Scholar
  32. Sharam S, Mohan A: Co-infection of human immunodeficiency virus (HIV) and tuberculosis: Indian perspective.Ind J Tuberc 2004, 51:5–16.Google Scholar
  33. Sharma S, Mohan A, Kadhiravan T: HIV/TB co-infection: epidemiology, diagnosis and treatment.Indian J Med Res 2005,121(4):550–67.PubMedGoogle Scholar
  34. Alzain B, Sharama P: Hemoglobin levels and protozoan parasitic infection in school children of Udaipur city (India).J Al Azhar Univ-Gaza (Na Sci) 2006, 8:35–40.Google Scholar
  35. Stephenson L: The public health significance ofTricuris trichuria.Parasitology 2000, 121:73–95. 10.1017/S0031182000006867View ArticleGoogle Scholar
  36. Cromoton D, Stenphenson L: In Hookworm infection, nutritional status and productivity. In .. Edited by: Chad GA, Warren K. Philadelphia: Taylor and Francos; 1990. 1: 236–245Google Scholar
  37. Osazuwa F, Michael A, Paul I: A significant association between intestinal helminth infection and anemia burden in children in rural communities of Edo state, Nigeria.N Am J Med Sci 2011,3(1):30–4. 10.4297/najms.2011.330View ArticlePubMedPubMed CentralGoogle Scholar

    38. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/2055-0928/1/5/prepub

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