Study area and period
The study was conducted at Gondar University Referral Hospital HIV care clinic from March to April; 2016. Gondar University Referral Hospital HIV care clinic is located in North Gondar administrative zone, Amhara National Regional state, which is about 727 km northwest of Addis Ababa, the capital city of Ethiopia. The hospital serves about five million people of the northwest Ethiopia. The HIV care service of the hospital was initiated in 2005 and has 7 outpatient rooms, one voluntary testing and counseling room, one pharmacy, and laboratory rooms. It has three adult ART clinic, one pediatric, one VCT and 2 adherence counseling clinic. Daily about 30–40 HIV positive clients visit the clinic. Since 2005, 7581 adults have enrolled in the clinic. Currently, about 4891 adults are actively following their treatment.
Source and study population
All HIV positive adults (≥18 years) who were enrolled for chronic HIV care at Gondar University referral Hospital ART clinic were the source population and those adults living with HIV/AIDS who came to Gondar University Referral Hospital for a follow up during the study period were our study population.
Inclusion and exclusion criteria
Adults age 18 and above living with HIV who visited the ART clinic during the study period were included in the study while pregnant women and adult with spinal problem (kyphosis) were excluded from the study.
Sample size determination and sampling procedure
The required sample size was calculated using single population formula \( n=\left({\left( z\frac{\alpha}{2}\right)}^2* p\left(1- p\right)\right)/ w2 \) [23], where n is the sample size, z is the value of standard normal distribution corresponding to a significant level of α of 0.005 which is 1.96, w is the margin of error which was taken as 5% and p is the estimated proportion of the target population by taking the prevalence of chronic energy deficiency as 25.2% [20] and adding 10% non- response error the final sample size computed was 319. In order to get sampling interval (k), the total population was divided by the sample size required. The data collection was planned to be finished within one month having 22 working days. To select our study participants, we considered the working days and the average daily patient flow in the ART clinic. The average daily patient flow was 30–40 (we took 35). The total expected number of patients to attend the clinic during the data collection period was 770 and to select 319 of our study participants, we used a systematic random sampling with a sampling interval of 770/319 ≈ 2. The first participant was selected using random starting point of lottery method. Subjects were chosen at regular intervals by adding two from each prior participant at their exit from the ART clinic.
Data collection tool and procedures
An interviewer administered pretested structured questioner was used to collect the socio demographic characteristics like sex, age, residence, marital status, educational level and occupation of study participants. Similarly, The household economic status of the participants was assessed by house hold wealth index questions which were extracted from EDHS 2011 [24]. It was assessed by using the selected household assets, house ownership, main materials of the roof and floor, toilet facility, source of drinking water and fuel, size of agricultural land, livestock ownership, microfinance bank account and receiving cash or food from safety net program. First variables were coded between 0 and 1. Then, principal component analysis was carried out. In the principal component analysis, the power of the variables to explain wealth status was determined step by step using the communalities values. Those variables having communality value of greater than 0.5 were used to produce factor scores. Hence, an Eigen value of greater than one was considered. Finally this factor scores were summed and ranked in to tertile as low, medium and high [25].
Tools for measuring the dietary diversity was adopted from FAO guidelines for measuring house hold and individual dietary diversity. Dietary Diversity Score (DDS) was assessed by asking the respondents to list all the food items they consumed in the last 24 h preceding the survey day. We used food groups in local context. Then the reported food items were classified into nine food groups. Respondents with dietary diversity score three and below were classified as having inadequate dietary diversity score while respondents with dietary diversity score above three were taken as having adequate dietary diversity score [26].
Anthropometric measurement (height and weight) was done to have information on the individuals’ Body mass index (BMI). Weight of the study participants was measured to the nearest 0.1 Kg of a standing beam balance. It was measured with lightly 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 measuring scale standing upright in the middle of board. It was measured following standard procedures. Participants’ takeoff their shoes, stand erect and look straight in horizontal plain. The occiput, shoulder, buttocks, and heels touched measuring board [27, 28] and it was recorded to the nearest 0.5 cm.. BMI was calculated as weight in kilograms divided by the square of height in meters (kg/m2). BMI was classified according to WHO classification [29]. Less than 18.50 kg/m2 taken as chronic energy deficiency (CED) and it was further classified as Mild CED if BMI was 17.00–18.49 kg/m2, Moderate 16.00–16.99 kg/m2 and severe less than 16.00 kg/m2. Patients who was considered as not having CED were normal (BMI 18.5–24.49 kg/m2), overweight (24.5–30.0 kg/m2) and obese (>30 kg/m2).
Stage of the disease, ART status and drug regimen were accessed on the patients’ medical chart. Blood sample was drawn from subjects as part of routine monthly ART follow up investigation to measure CD4 cell count and Hemoglobin level.
Laboratory
Hemoglobin was measured with Cell Dyne hematology analyzer (US). Hemoglobin level <13 g/dl for men and < 12.0 g/dl for women patients was considered as anemic [30].CD4+ T cell count was measured with BD FACS machine (US) and categorized according to different literatures by taking 200 as a cutoff point [31].
Data processing and analysis
Data were checked for completeness, entered and coded using EPI-INFO version 7 software. Analysis was carried out using Statistical Package for Social Science (SPSS) version 20 statistical program. Frequencies and graphs were used to explore the data. Binary logistic regression analysis was used to identify the confounders. Variables with a p-value of <0.2 and variables which were highly significant in other studies were entered to multi-variable logistic regression (Back ward likelihood ratio variable selection method) to identify factors which have statistically significant association. Adjusted odds ratio (AOR) with 95% confidence interval and p-value <0.05 was used to show association between explanatory variables and dependent variable. The fit of the model was assessed using the Hosmer-Lemeshow goodness-of-fit test and p-value > 0.05 was taken as a cutoff point.
