Project Title: Strengthening Uganda Systems for Treating AIDS Nationally

Project Title: Strengthening Uganda Systems for Treating AIDS Nationally (SUSTAIN) Study title: Assessment of Dietary Patterns for People Living with HIV seeking health services from Regional Referral Hospitals in Uganda

Twaha Rwegyema, BSC. Human Nutrition and Dietetics, MPH HIV/AID Nutrition Program Officer, SUSTAIN Project, University Research Co., LLC – Center for Human Services Plot 7, Ntinda View Crescent, Naguru. P.O. Box 28745, Kampala - Uganda Email: [email protected], Tel: +256-7540601879

Martin K Mbonye, PhD Senior Monitoring and Evaluation Advisor SUSTAIN Project, University Research Co., LLC – Center for Human Services Plot 7, Ntinda View Crescent, Naguru. P.O. Box 28745, Kampala - Uganda Email: [email protected], Tel: +256-752368550

Dr. Alima Hillary, MD, MPH Care & Treatment Advisor, SUSTAIN Project, University Research Co., LLC – Center for Human Services Plot 7, Ntinda View Crescent, Naguru. P.O. Box 28745, Kampala - Uganda Email: [email protected], Tel (Cel): +256-772-412910

Dr. Augustin Muhwezi, MD, MPH Chief of Party, SUSTAIN Project, University Research Co., LLC – Center for Human Services Plot 7, Ntinda View Crescent, Naguru. P.O. Box 28745, Kampala - Uganda Email: [email protected], Tel: +256-774194514

August 2016 Table of Contents List of Acronyms ...... iii

Abstract ...... iv

Operational definitions ...... v

1.0 Introduction ...... 1

1.1 Background ...... 1

1.2 Problem statement ...... 3

1.3 Justification ...... 4

2.0 Objectives ...... 5

2.1 Main objective ...... 5

2.2 Specific objectives ...... 5

3.0 Methods...... 6

3.1 Study design ...... 6

3.2 Study area...... 6

3.3 Study population ...... 6

3.4 Sampling and sample selection criteria ...... 6

3.4.1 Sample size determination ...... 6

3.4.2 Sample size determination formula ...... 7

3.4.3 Sample selection ...... 8

3.5 Inclusion and exclusion criteria ...... 9

3.5.1 Inclusion criteria ...... 9

3.5.2 Exclusion criteria ...... 9

3.6 Study variables ...... 9

3.6.1 Dependent variables ...... 9

3.6.2 Independent variables ...... 10

3.7 Data Management ...... 10

3.7.1 Data collection procedures ...... 10

3.7.2 Training of Research Assistants ...... 11

3.7.3 Tools ...... 11

3.7.4 Pretesting of the tool ...... 12

3.7.5 Field editing of the data ...... 12

3.7.6 Data entry ...... 12

3.7.7 Data coding ...... 12

3.7.8 Quality control ...... 12

3.8 Data Analysis ...... 13

3.8.1 Analysis techniques, presentation of data and tests for significance ...... 13

3.9 Ethical considerations ...... 13

3.9.1 Ethical review and approval process ...... 13

3.9.2 Informed consent ...... 14

3.9.3 Confidentiality ...... 14

3.10 Study Limitations ...... 14

3.11 Report writing ...... 14

4.0 Dissemination of report findings ...... 15

5.0 Study Timeline ...... 15

6.0 References ...... 16

List of Acronyms

AIDS Acquired Immunodeficiency Syndrome ART Antiretroviral Therapy BCC Behavioral Change Communication CDC Center for Disease Control and Prevention

HDDS Household Dietary Diversity Score HIV Human Immune Virus

IDDS Individual Dietary Diversity Score NACS Nutrition Assessment Counseling and Support PLHIV Persons Living with HIV

REE Resting Energy Expenditure SUSTAIN Strengthening Uganda Systems for Treating AIDS Nationally TEE Total Energy Expenditure USAID United States of Agency International Development

iii

Abstract

Introduction:

Interactions between food insecurity, malnutrition, and HIV/AIDS are well established. High rates of malnutrition among HIV/AIDS infected children have been widely reported. In addition, several studies consistently show that malnutrition is a strong independent predictor of mortality among people living with HIV (PLHIV). Many factors associated with wasting/malnutrition among PLHIV including metabolic alterations have been reported. Some studies have also reported a significantly positive correlation between food assistance and mean weight gain among PLHIV. The Uganda Ministry of Health has developed nutrition counseling job aides that focus mainly on nutrients and food groups. But these job aides are too generic and include limited and general examples of food types per food group and nutrient type with less emphasis on specific foods commonly available in different geographical areas. Understanding the different common types of foods available in different regions is key to understanding the dietary patterns for PLHIV. This is key to promoting nutrition counseling guided by food types easily accessed by the PLHIV and could improve the nutrition status of the PLHIV. This study aims at assessing dietary patterns among PLHIV accessing HIV care services at USAID/SUSTAIN project supported Regional Referral Hospitals (RRH) in Uganda.

Methods:

This will be a retrospective unmatched case control study. The assessment will target 583 (147 Cases and 436 Controls) HIV infected individuals attending HIV clinics at eleven USAID/SUSTAIN supported Ugandan RRH.

Implication:

The findings from this study will guide development and implementation of interventions for improving dietary patterns of PLHIV based on food types available and commonly consumed in a specific geographical locality. The current job aides, health worker training/orientation curriculum and counseling messages will also be improved and focused on regional specific food types. The study results will also contribute to the limited literature on dietary patterns for PLHIV in Uganda.

Operational definitions

"Wasting syndrome" is defined as a weight loss of at least 10% that is not attributable to a concurrent condition other than HIV infection itself.

A case is a PLHIV accessing HIV care services (Pre ART or ART) at USAID/SUSTAIN supported hospitals who was diagnosed with malnutrition.

A control is a PLHIV accessing HIV care services (Pre ART or ART) at USAID/SUSTAIN supported hospitals who did not have malnutrition or whose nutrition status was normal.

Dietary pattern is defined as the quantities, proportions, variety or combination of different foods, drinks, and nutrients in diets, and the frequency with which they are habitually consumed.

Dietary diversity refers to the consumption of a variety of food groups considered an indicator for dietary quality and general nutritional adequacy.

Food group is defined as a collection of foods that share similar nutritional properties or biological classifications. For example; fruits, dairy and dairy products, Legumes, Green Leafy Vegetables, tubers and roots, cereals, animal meats among others.

Nutrient is defined as a substance that provides nourishment essential for growth and the maintenance of life. Examples include; protein, carbohydrates, mineral and vitamins.

Food type is defined as any nutritious substance that people or animals eat or drink, or that plants absorb, in order to maintain life and growth. Examples include; Matooke, cassava, Irish potatoes, meat, fish, chicken, vegetables, fruits etc.

1.0 Introduction

1.1 Background

The U.S. Centers for Disease Control and Prevention (CDC) recognized wasting as an AIDS- defining condition in 1987. The "wasting syndrome" is defined as a weight loss of at least 10% that is not attributable to a concurrent condition other than HIV infection itself.1

Prevalence of wasting as an initial AIDS-defining diagnosis was estimated to range up to 37% in surveys performed before the advent of effective ART.2 Some reports suggest that the incidence of wasting has declined since the introduction of effective ART,3 but data from other studies indicate that wasting remains a significant complication, even in populations with widespread access to effective ART.4-5 A report from a large cohort study suggested that although weight loss is an infrequent occurrence, a more gradual, progressive loss of lean tissue continues in many subjects.6

In addition to weight loss, depleted levels of body cell mass, which contains the metabolically active tissue, have been associated with increased risk of mortality in patients with HIV infection.7-8 It is important to note that death from malnutrition in patients with AIDS occurred at the same degree of depletion of weight and body cell mass (66% and 54% of normal, respectively) as was seen in historical reports of death from starvation.9

Weight loss in HIV infection is characterized by depletion of both fat and lean tissue. Rapid weight loss has been associated with acute infections, whereas more gradual weight loss has been associated with malabsorptive disorders. Factors demonstrated or hypothesized to contribute to wasting/malnutrition include metabolic alterations, anorexia, malabsorptive disorders, hypogonadism, and excessive cytokine production.10

HIV infected adults have 10−30% higher energy requirements than a healthy adults without HIV, and 50−100% higher in infected children as compared to their counterparts.11 Decreased energy intake, coupled with inappropriately elevated Resting Energy Expenditure (REE), is the main factor in negative energy balance that results in weight loss.12 Studies using stable isotope techniques indicate that total energy expenditure (TEE) is not significantly elevated in weight- stable patients with HIV infection, when compared to healthy adults.13 Patients losing weight have been found to have decreased levels of TEE, despite elevated rates of REE, reflecting a decrease in physical activity levels. Other metabolic alterations in HIV-infected individuals, include: increased and decreased14 rates of protein turnover; decreased rates of muscle protein synthesis; and increased rates of de novo hepatic lipogenesis15 lipid flux, and oxidative and non- oxidative lipid disposal. As of yet, no mechanistic relationship has been demonstrated between these or other metabolic alterations and wasting.

Furthermore, anorexia leading to inadequate dietary intake results from a variety of factors caused by HIV infection itself, secondary infection, and treatments for either. Painful oral and esophageal complications such as candidiasis and aphthous ulcers can reduce voluntary food intake. Nausea is a frequent adverse effect of medications as well. HIV-infected men with wasting have also been reported to have significantly lower total and free testosterone levels than weight-stable men.16 Decreased free testosterone levels have also been found in HIV-infected women with wasting. In addition to malnutrition, a variety of commonly used medications, including ketoconazole, cimetidine, ganciclovir, and megestrol acetate have been associated with low testosterone levels.17 Chronic diarrhea and malabsorption are common in HIV-infected patients. Where ART is available, diarrhea associated with intestinal pathogens has decreased, whereas ART-associated diarrhea has increased. In addition to a loss of calories associated with malabsorption, diarrhea can secondarily contribute to weight loss by discouraging food intake.18

Cytokine disturbances are implicated in the metabolic disorders and wasting that accompany HIV infection.19 For example, alterations in triglyceride (TG) metabolism, such as hypertriglyceridemia, slowed TG clearance, and increased de novo hepatic lipogenesis, correlate with elevated circulating levels of interferon alfa (IFN-alfa).20 One longitudinal study linked lean tissue loss to TNF-alpha and IL-1 beta (production by circulating mononuclear white blood cells in men with HIV infection 21

Nutrition education at early stages of HIV infection gives a person chance to build up healthy dietary patterns/habits and ensure improved food security in an effort to maintain a good nutritional status.22 While adequate nutrition is vital for the health and survival of all individuals regardless of their HIV status, those infected are at a higher risk of infections and with more dietary needs to prevent wasting and other nutrient deficiencies. Prompt diagnosis and treatment of these conditions, including use of antiretroviral treatment (ART) when indicated, can contribute to improved nutrition and health.23

Dietary counseling can help individuals identify target energy intake and food choices to suit individual tastes, practices, and tolerances; maintaining energy intake, even during periods when eating is not pleasurable; and can give patients techniques for managing HIV- or medication- related symptoms such as anorexia, early satiety, nausea, vomiting, diarrhea, food intolerances, and oral or esophageal ulcers.10

Integrating nutrition interventions into HIV/AIDS Care programs prolongs patient survival and reduces death due to malnutrition among PLHIV, receiving ART24 and Prophylaxis. Nutrition interventions like Nutrition Education and Counselling (NEC) are vital in HIV/AIDS care. In resource limited settings, NEC empowers PLHIV to modify their diets, using locally available,

nutrient dense and culturally acceptable foods to maintain good health, improve their nutritional status25 and daily functioning. Through improved Knowledge, Attitude and Practices, PLHIV can ably plan to utilize the limited resources and modify diets to boost their immunity, better manage the disease and improve response to ART and other treatment26,27.

Because poor knowledge and dietary practices significantly contributes to the rapid progression of HIV to AIDS, nutrition is critical in combating HIV/AIDS and interventions can be implemented throughout prevention, care, treatment and support strategies28. Uganda has made significant achievements in the care, treatment and support for PLHIV but for nutrition knowledge improvement, which is essential in HIV/AIDS Care remains a challenge29. In Uganda, the nutrition knowledge gap exists among PLHIV due to inadequate nutrition education and counselling, as part of their Care at health units and limited knowledge on use of the locally available food30 to manage the disease. Consequently, some of our PLHIV are not aware of the importance of nutrition to maintain good health.

While nutrition counselling, care, and support is integral to comprehensive HIV care for PLHIV31, it has not been prioritized in Uganda. The policies, guidelines, and strategies developed address integration of nutrition service delivery. However, inadequate nutrition counseling, and knowledge on use of the locally available foods32 (Gillespie S. et al., 2001) to maintain good health underpins the existence of malnutrition among PLHIV, which would otherwise be prevented.

Addressing food and nutrition security for HIV infected individual at different levels of care is therefore key in ensuring improved outcomes and adherence to treatment. The Ministry of Health for Uganda adapted the Nutrition Assessment Counseling and Support (NACS) framework with an aim of integrating nutrition services into HIV care and beyond.33 This has been a success with the most recent development being the integration of nutrition variables in majority of HIV care tools and reporting systems both at health facility and national levels. However, the support and service delivery has been biased to identification of malnourished clients and managing them on therapeutic food, which is usually not sustainable. The revised Ministry of Health NACS counseling cards and job aides focus on food groups and information giving. This therefore limits health workers to providing information on locally and regionally available foods. Further still, there is limited literature on quality of nutrition counseling provided, especially with the use of these counseling materials.

1.2 Problem statement

HIV/AIDS continues to be a major problem in Uganda. The most recent two rounds of national AIDS Indicator Surveys show that HIV prevalence in the general population in Uganda

increased from 6.4% in 2004/5 to 7.3% by 2011, while the 2013 UNAIDS estimates show that HIV prevalence has stagnated around 7.4% in 2012/2013. However, there has been a gradual increase in the number of HIV positives accessing ART from about 330,000 (23.6% of the 1.4 million people estimated PLHIV) in 2011 to about 750,896 (50.1% of the 1.5 million people estimated PLHIV) in 201434. The United States Agency for International Development (USAID) finances University Research Co., LLC (URC) to implement Strengthening Uganda Systems for Treating AIDS nationally (SUSTAIN) project. Since 2010, SUSTAIN has been supporting 11 RRH to integrate nutritional assessment, counseling and support (NACS) into HIV/AIDS care to improve clinical outcomes of PLHIV accessing HIV care at these hospitals. Nationally, the prevalence of malnutrition among PLHIV has been declining. As at end of March 2016, the burden of acute malnutrition was estimated to be 3% (1,539) among the 51,359 PLHIV enrolled and active in HIV care at SUSTAIN supported RRH.35 Despite the observed decrease in malnutrition levels, this burden is still high. Effective HIV/AIDS care requires good nutrition and food intake to ensure a holistically better care and health of the PLHIV. It is generally accepted that a diversity of foods provides a healthier diet and eating it is associated with better health outcomes such as reduced malnutrition and mortality. Since 2006, Uganda has developed and modified Standard Operating Procedures (SOP)/counseling aides to support nutritional counseling among PLHIV. These SOP/aides provide some examples of common food types in different nutrient category. However, the information provided in these materials is limited in detail and somewhat generic with fewer examples compared to the numerous food types produced in the various geographical regions of Uganda. With this limited information, these SOP/aides tend to limit their focus on counseling about a “balanced diet” with less emphasis on the various foods available and accessible to the clients in their geographical locality and the nutritional value in these foods that can provide a balanced diet. The information from this study will help avail more information on various food types consumed by PLHIV in different geographical locations of Uganda and enable to compare dietary patterns of the PLHIV who are malnourished to those with normal nutritional status. This information will also help determine the various factors that explain the differences in dietary patterns between the PLHIV who are malnourished and with normal nutritional status and explain how PLHIV cope during food scarcity.

1.3 Justification

Streamlining dietary and nutrition-specific counseling especially among malnutrition vulnerable HIV positive patients requires provision of targeted-specific information based on regional differences and socio-economic variations. This assessment therefore seeks to understand the variations in dietary patterns of people living with HIV (PLHIV) who access HIV care services at the 11 different USAID/SUSTAIN supported RRH in Uganda. This study will determine the dietary diversity score among PLHIV in care at Regional referral Hospitals in Uganda. It will

also provide information on the relationship between dietary diversity and socio-demographic, economic and HIV care related factors among PLHIV. The findings from this study will provide various stakeholders involved in HIV/AIDS programming care and policy makers with additional information to enable design of appropriate nutritional interventions to improve HIV nutritional care programs particularly among adults. The information from this study could also inform updating of the current NACS SOP/aides taking into consideration additional food types absent from the current versions and also enable provision of targeted messages within each region.

2.0 Objectives

2.1 Main objective

The main objective of the study it to assess the dietary patterns for People Living with HIV seeking health care from RRH of Uganda.

2.2 Specific objectives

1. To identify the foods commonly consumed by PLHIV attending HIV clinics at RRH in Uganda. 2. To compare dietary patterns of malnourished and non-malnourished HIV patients attending HIV clinics at RRH in Uganda. 3. To explore demographic, socio-economic and hospital care factors associated with dietary patterns among HIV patients attending HIV clinics at RRH in Uganda. 4. To identify and compare coping mechanisms during food scarcity between the malnourished and non-malnourished HIV patients attending HIV clinics at RRH in Uganda.

3.0 Methods

3.1 Study design

This will be an unmatched case-control study involving HIV infected clients irrespective of their ART status who are receiving HIV care services at 11 SUSTAIN supported regional referral hospitals in Uganda. The cases will include malnourished HIV infected clients and controls HIV infected clients with a normal nutrition status.

3.2 Study area

The study will be conducted in the following 11 USAID/SUSTAIN project supported regional referral hospitals: Fort Portal, Gulu, Hoima, Jinja, Kabale, Lira, Arua, Mbale, Moroto, Mubende and Soroti to strengthen systems for nutrition service delivery. In total, there are 14 RRH in Uganda, the other 3 being: Masaka which USAID/SUSTAIN partially supports with TB/HIV and VMMC services and Mbarara and Naguru Uganda-China Friendship hospital which USAID/SUSTAIN does not support at all. In the Ugandan health service delivery system tier, RRH hospitals are right below two national referral hospitals. The two National Referral Hospitals, Butabika hospital which was established in 1955 and the only mental health hospital in the country; and Mulago hospital which is the biggest National Referral Hospital. These national referral hospitals provide comprehensive specialized and teaching services and engage in high level health/medical research. RRH are semi-autonomous, serve a population of approximately 3,000,000 people and offer specialist clinical services such as psychiatry; Ear, Nose and Throat (ENT); ophthalmology, higher level surgical, medical services, and clinical support services (laboratory, medical imaging, and pathology). They are also involved in nursing teaching and research.

3.3 Study population

The study population will specifically include HIV infected clients irrespective of their age and ART status (Pre-ART and/or ART) that have been active in HIV care at least six months preceding the data collection. A case will be a PLHIV who is malnourished and a control will be one with normal nutritional status.

3.4 Sampling and sample selection criteria

3.4.1 Sample size determination

The sample size has been determined using a formula for calculating sample size for a case- control studies which was developed in 1982 by Schlesselman (Schlesselman, 1982)36;

Table 1: Sample size per health facility Regional Active Acutely Normal Total Normal Malnourish Referral clients malnou nutrition Sample nutrition ed sample Hospital in care rished status size status sample size (Case) name size (Control)

Arua 6,756 87 4,329 52 43 9 Fort Portal 7,736 86 6,651 75 66 9 Gulu 4,885 177 4,682 66 48 18 Hoima 5,028 128 4,750 61 48 13 Jinja 3,081 60 2,952 36 30 6 Kabale 3,357 91 2,426 34 25 9 Lira 9,888 399 7,625 118 79 39 Mbale 4,197 177 3,737 56 38 18 Moroto 600 71 349 11 4 7 Mubende 4,516 120 4,292 55 43 12 Soroti 1,315 69 1,108 19 12 7 Total 51,359 1,465 45,444 583 436 147

3.4.2 Sample size determination formula

The formula used is for sample size for difference in proportions.

Formula:

Where:

 n is sample size in the case group  is the ratio of controls to cases, where r is the number of controls needed per case.  is the measure of variability, where is average proportion of the population exposed to an event of interest in the controls.  is the desired power  is the desired level of statistical significance

 is the effect size

Formula ii.

And average proportion exposed in the cases and controls =

Assumptions

 50% as proportion of non-malnourished HIV positive patients with low Individual Dietary Diversity Score (IDDS) - .  Desired power of the study is 80%.  Desired level of statistical significance is 95%.  Ratio of Controls to Cases is 3 to 1.

Calculations

 With 50% being the estimated proportion of non-malnourished HIV positive patients with low IDDS ( ).  At the desired power of the study of 80%, = 0.84.  At the desired level of statistical significance of 95%, =1.96.  Using a Controls to Cases ratio of 3 to 1. This ratio was chosen because it provides sufficient study power to ensure that meaningful and reliable inferences can be drawn from the study. At ratio 1:4 (case: control) and beyond, the sample generated does not generally add more power to the study. ( =1.33)  Using 50% being the estimated proportion of non-malnourished HIV positive patients with low IDDS and assuming we would like to detect an odds ratio of 2.0. = = 0.5. Using Formula ii above, = = 0.667 which is the proportion of the malnourished HIV positive patients with low IDDS. Average number of HIV positive patients with low IDDS = (0.50+0.667)/2 = 0.583.  Variability = 0.243.  Estimated sample size for Cases = 147  Estimated sample size for Controls = 436  Total estimated sample size =145+435 = 583.

Proportional to size allocation method was used to obtain the contribution of cases and controls to the total sample size for each hospital involved in the study as per the Table 1 above.

3.4.3 Sample selection

Selection of study participants will commence immediately after this study has been approved by the Uganda National Council for Science and Technology (UNCST). At each study hospital, the

eligible study participants (both cases and controls) will be selected consecutively until the required sample size of cases and controls has been attained. Two trained research assistants will collect data at each hospital with overall guidance from the principal investigator. Study participants will be identified during the HIV clinic days. Only PLHIV who consent and/or ascent to the interview will be interviewed. Appointments for clinic visits and choice of the PLHIV to visit the HIV clinic is a random process which is not selective to any specific category of the population under study. We therefore do not anticipate selection bias due this suggested sample selection criteria.

3.5 Inclusion and exclusion criteria

3.5.1 Inclusion criteria

 HIV infected clients who attend the HIV clinic during the course of the study, and have been active in care at least six months preceding the day of data collection will be included in the study until the required sample size of both the cases and controls at the respective study hospitals has been achieved.

 The participants will be selected irrespective of their age and ART status.

 HIV positive minors who come to the HIV clinics during the data collection process i.e. before the required sample has been obtained and have been active in care six months preceding the survey will be eligible for the interview.

3.5.2 Exclusion criteria

 HIV clients who do not attend the clinic during the course of the study will not be considered in this study. All patients should be able to consent and respond, the younger patients between 12 and 17 will ascent to the study after consent of their guardians or caretakers who have accompanied them to the hospital, while those below 12 years will only need the consent of their guardians or caretakers who have accompanied them to the hospital.

3.6 Study variables

3.6.1 Dependent variables

For objectives 2 and 3, the dependent variable will be IDDS. IDDS will be used as a proxy measure of dietary food patterns. It will be categorized in the following terciles: Low IDDS (1 – 3 food groups), Medium IDDS (4 – 5 food groups) and High IDDS (6 or more food groups). To

address objective 4, the dependent variable will while food security categorized as food secure or food insecure.

3.6.2 Independent variables

The independent variables will be demographic (age, sex, body mass index), socio-economic (marital status, occupation, level of education, income, ownership of household items,) and hospital care factors (ART status, functional status, ART adherence status, WHO stage, CD4 count, ART regimen, history of opportunistic infections, pregnancy status if female, disclosure status, nutritional counseling status, nutritional status history, access to nutrition information, source of nutrition information), and food shortage coping mechanisms (income and expenditure and food management strategies).

3.7 Data Management

3.7.1 Data collection procedures

Data will be collected using a semi-structured questionnaire (Appendix 2). This questionnaire will be administered to the respondents through confidential face-to-face interviews. The questionnaire includes a 24 hour- recall and a food frequency questionnaire to determine the IDDS for the respondents. The tool will also capture data on demographic, socio-economic, weight gain trends, food security status and food insecurity coping mechanisms and hospital care variables e.g. ART status, adherence to ART, any history of opportunistic infections, appointment keeping etc. For eligible minors, their responses will be elicited from caretakers or guardians who will have brought them to the hospital. The HIV clinic staff will closely work with the research assistants to inform them of presence of potential respondents. Irrespective of the nutritional status (malnourished or normal), the research assistants will work with the clinic’s clinical staff to ascertain the nutritional status using MUAC and BMI. For children below five years, height and weight will be measured to determine their wasting levels. Children with Z- scores of <-3SD will be categorized as severe acutely malnourished (SAM), >-3 but <=-1 SD as moderate acutely malnourished (MAM) and >-1 as having normal nutritional status (Normal). For children aged 5 to 18 years, BMI for age will be determined and similar Z-scores as for children less than five years will be used to categorize them. For adults greater than 18 years, BMI scores will be obtained and individuals will be categories as follows: <18kg/Meter square will be acutely malnourished and >18 – 24 kg/Meter as normal. MUAC tapes will also be used to confirm the nutritional status of respondents as follows: Red as SAM, Yellow as MAM and Green as Normal. All respondents with SAM and MAM will be categorized as malnourished. In the questionnaire, questions for only adults have been clearly specified with example including marital status and income. The 24 hour food recall and food frequency part of the questionnaire will mainly elicit responses on different food types taken under each of the various food groups.

For example, under food group cereals and grain products, different food types such as maize, wheat, rice, millet are listed. Under the same section, the respondent will be required to mention how many times each of the food types was taken over the last 24 hours and past six days (never, once, 2-3 times) as well as what was the source of the food.

3.7.2 Training of Research Assistants

Twenty two research assistants (two per hospital) will be recruited to conduct data collection. Each research assistant should have clinical experience in managing HIV positive patients, conversant with nutritional aspects and will not be a staff of the hospital where the study will be conducted. The research assistants will then be oriented on how to administer the data collection tool to ensure quality data is collected. The training will be conducted at one central location in Kampala. All research assistants will be trained together to enable them provide feedback. The training will be conducted by the study investigators assisted by a nutrition officer from the Uganda ministry of health. The principal investigator is also an experienced nutritionist. The training will mainly focus on how to administer the questionnaire and the consent form, how to identify participants, ensuring confidentiality during interviews and when transporting completed questionnaires and how to conduct field data cleaning. During this training the research assistants will revise all the tools for better and common understanding of all questions. They will also receive tips on questioning and probing techniques to ensure they minimize loss of intended meaning of different questions and how to fill the questionnaire. Part of the training of research assistants will include pre-testing the questionnaire.

3.7.3 Tools

A semi- structured data collection tool has been developed and is attached to this protocol as Appendix 2. It is accompanied by the consent form with assent options attached to this protocol as Appendix 1. The main questionnaire includes the following major parts: basic demographic and socio-economic variables (age, sex, body mass index, marital status, occupation, level of education, income, ownership of household items,) and HIV care status and services (ART status and start date, functional status, ART adherence status, WHO stage, CD4 count, ART regimen, history of opportunistic infections, pregnancy status if female, disclosure status), nutrition status and services (nutritional counseling status, nutritional status history, access to nutrition information, source of nutrition information), Frequency, diversity and source of food intake (food types under each food group, the times each of these food types were eaten during the past six days and 24 hours and source of the food), food availability ( access to agricultural land, crops grown during the last season, main crops grown during the year, amount of food harvested and biggest constraints in agriculture) and food shortage coping mechanisms (income and expenditure and food management strategies).

3.7.4 Pretesting of the tool

Pretesting of the tool will take place at Kawolo hospital, one of the general hospitals supported by the SUSTAIN. Written permission to pretest the data collection tool will be sought from the hospital management. The research assistants will take part in pretesting of the tool as part of their training.

3.7.5 Field editing of the data

While in the field, the research assistants will on a daily basis take time to review the collected data and identify and correct errors in order to ensure good quality of the data collected. The two research assistants collecting data at each hospital will review each other’s completed questionnaires for accuracy, consistency and completeness on a daily basis. Anomalies will be corrected appropriately by either contacting respondents by telephone or on person at the respondent’s convenient time within a period of one week following the interview. Some anomalies will be corrected by reviewing the patient’s HIV care files where possible.

3.7.6 Data entry

All data will be entered by a dedicated and trained Data Entry Assistant based at the USAID/SUSTAIN offices in Kampala. All data will be entered into an EpiData® software svrsion 3.1. To check if the responses and codes entered are consistent and within acceptable range within the database, validation checks will be applied by running frequency tables and results used to edit incorrect entry fields.

3.7.7 Data coding

Most of the data on the data collection tool is coded. However, for responses to open ended questions, the project team headed by the nutritionist at the USAID/SUSTAIN offices in Kampala will determine the codes used and appropriately code the data.

3.7.8 Quality control

The data entry screen in Epidata will be embedded with skip patterns as well as out of range and “data required” probes where necessary. This is to ensure that data is within an acceptable range, available data is all captured and where data is not needed, it is automatically skipped. Double data entry will also be done and entered data compared. Where discrepancies are identified, questionnaires will be identified and corrections made accordingly.

3.8 Data Analysis

3.8.1 Analysis techniques, presentation of data and tests for significance

Descriptive statistics will be used to describe clients’ characteristics. Continuous variables will be described using means with standard deviations or median with inter-quartile range (IQR), while categorical variables will be analyzed using frequencies and percentages. Associations will be examined using univariate logistic regression analysis. All variables with a P-value <0.2 and those significant on the bivariate analysis will further be considered in the Multivariable logistic regression model. Results of multivariable and univariate analysis will be respectively presented as crude and adjusted odds ratios with corresponding confidence intervals and p-values (alpha =0.05) to determine factors independently associated with the dependent variables after controlling for confounding effects and interaction. All analyses will be conducted using Stata version 12 (Stata Corp, College Station TX, USA).

3.8.2 Nutrition assessment and dietary patterns analysis

Data collected on anthropometric measures including weight, height and MUAC will be analyzed based on the World Health Organization Standards for nutrition status. Weight and height will be computed to the Body Mass Index for adults above 19 years of age and BMI-for- age will be determined for those 5-19 years. WHO Anthroplus V 1.0.4 software will be used to run the analysis.

The dietary patterns data will be aggregated into food groups using Microsoft Excel to estimate the food security status of the households compared against WHO ratings. The 24-hour recall information will be analyzed using ProPAN and Optifood software to determine the dietary adequacy for HIV clients accessing healthcare. The analysis will be used to determine the IDDS and not Household Dietary Diversity Score (HDDS). Dietary diversity is a qualitative measure of food consumption that reflects household access to a wide variety of foods, and is also a proxy of the nutrient adequacy of the diet for individuals. IDDS will be created by summing either the number of individual foods or food groups consumed over the 24 hour recall period.

3.9 Ethical considerations

3.9.1 Ethical review and approval process The study protocol received approval from URC IRB and requires the Ugandan local IRB for approval. After approval by a Ugandan local IRB, the study protocol will then also be submitted to the Uganda National Council for Science and Technology (UNCST) for final approval. Prior to data collection, the approval letters will be shared with the directors of the hospitals where the

study will be conducted. Approval to do data collection will be sought from the hospital directors.

3.9.2 Informed consent

Informed consent will be sought from study participants, explaining to them the purpose of the study and re-assuring them of the confidentiality of the study. A consent/ascent form is attached to the protocol as Appendix I. A decision not to participate in the study by potential respondents will be respected. For minors eligible for the study who are aged under 12 years, guardians or parents who have accompanied them to the hospital will be requested to consent on their behalf. For eligible children aged 12 to 18 years, parents who have accompanied them to the hospital will be asked to consent on their behalf and them to ascent to participate.

3.9.3 Confidentiality

Interviews will be conducted in a separate room and between only the interviewer and the respondent/guardian/caretaker. Unique identifiers will only be used instead of names and other identifying information. Patients will get an explanation that data will strictly be used for research purposes and only the interviewer, the nutritionist and data entrants will have access to the data for purposes of collection, data quality, coding and entry. The research assistants will seal the collected data in envelopes and submit them to the Clinical Care Coordinators for storage into the black boxes at the facilities. Collected data will be transported to the USAID/SUSTAIN offices in sealed black boxes and strictly by USIAD/SUSTAIN drivers when they visit the sites.

3.10 Study Limitations

Because the study is based on the respondent’s memory, it difficult to control for memory lapse as information cannot be verified for accuracy. The tools might also not accurately capture all the foods consumed in the different regions.

3.11 Report writing

The report writing process will focus on presenting results as per this study’s objectives and key recommendations/messages will be made for consideration and inclusion during nutrition counseling protocols. The report will include tables and figures presenting the results with required descriptions.

4.0 Dissemination of report findings Results of this work will be presented to various stakeholders involved in implementing HIV care and Nutrition programs in Uganda and to the MOH. Abstracts will also be written and submitted to various relevant local and international conferences. Manuscripts will be written and submitted to peer review journals for online publication. Results will also be shared with the hospitals involved in this research. A stakeholders meeting will also be held to disseminate the findings of this research.

5.0 Study Timeline Activity Month 1 Month 2 Month 3 Month 4 Month 5

Operations W1 W W W W1 W W W W W W W W W W W W W W W4 2 3 4 2 3 4 1 2 3 4 1 2 3 4 1 2 3 Drafting of concept and tools Preparation for Data Collection, pretesting data collection tools (qualitative interview guide) Data collector training Data Collection Travel & Data collection Data Entry Data Analysis and Report Writing Analysis and drafting of report Sharing of results with project team Drafting of manuscripts for wider dissemination/publication

6.0 References

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