RENEWAL Regional Workshop 2010, Cape Town Food Security and Nutrition among People Living with HIV in Uganda: Emerging Res...
Food insecurity and HIV: What do we know?  <ul><li>Food insecurity is associated with: </li></ul><ul><ul><li>HIV transmiss...
Rationale for Nutrition Programs <ul><li>High geographic overlap between HIV prevalence, malnutrition, and chronic food in...
Nutrition Program Responses <ul><li>HIV services integrating food and nutrition components </li></ul><ul><ul><li>Food by P...
Food Insecurity, Undernutrition and HIV: 3 key  questions <ul><li>What are the determinants of undernutrition among PLHIVs...
3 Key Components (2007-2010) <ul><li>Conduct a  prospective  impact evaluation of a WFP food assistance program </li></ul>...
Study 1: Food Effectiveness Study <ul><li>Objective: To estimate the effectiveness of food support (in the form of a WFP H...
Outcomes of Interest in Programs <ul><li>Individual </li></ul><ul><li>Disease progression (CD4 count, WHO stage) </li></ul...
Emerging Results <ul><li>Previous studies consistently show malnutrition as a strong predictor of mortality </li></ul><ul>...
Determinants of Undernutrition <ul><li>Mean BMI: 20.5 (± 2.6) kg/m 2 ; MUAC: 267 (± 28) mm; DDS: 6.3 (± 1.7) food groups <...
Determinants of Undernutrition <ul><li>HIV-infected individuals living in severely food insecure HH have a 1.9 times great...
Evaluating Pathways to Undernutrition:  Path Analysis Notes: Numbers in parentheses are standard errors. For both Path 1 (...
Nutritional Determinants of Disease Severity <ul><li>Predictors of CD4 count <350 cells/uL </li></ul><ul><li>Diet quality,...
Study 2: Retrospective Evaluation of the TASO database <ul><li>TASO electronic monitoring data system </li></ul><ul><ul><l...
Impact of Food Assistance on Weight Gain ** significant at 1% ; *significant at 5% ; + significant at 10% a  Absolute valu...
Impact of Food Assistance on Weight Gain ** significant at 1% ; *significant at 5% ; + significant at 10% a  Absolute valu...
Preliminary Conclusions <ul><li>Ensuring diet quality, in addition to food access, should be a focus for programs </li></u...
Looking Ahead: Knowledge Gaps to Improve Programs <ul><li>Composition of nutritional support, and package of services (foo...
Key Publications (2007-date) <ul><li>HIV and Livelihood Programming </li></ul><ul><li>Kadiyala S, Rawat R, Roopnaraine T, ...
Upcoming SlideShare
Loading in …5
×

Food and nutrition assistance to PLHIV

1,498 views

Published on

Presentation made at the Sixth RENEWAL Regional Workshop: A decade of work on HIV, food and nutrition security. By Rahul Rawat and Suneetha Kadiyala

0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
1,498
On SlideShare
0
From Embeds
0
Number of Embeds
3
Actions
Shares
0
Downloads
0
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide
  • The indirect effect of food insecurity on BMI, mediated through dietary diversity is negligible, and almost entirely a result of the direct effect of food insecurity on BMI
  • Food and nutrition assistance to PLHIV

    1. 1. RENEWAL Regional Workshop 2010, Cape Town Food Security and Nutrition among People Living with HIV in Uganda: Emerging Results from the IFPRI/RENEWAL-TASO Collaboration ----------------------------------------------------------------------------------------------------- Suneetha Kadiyala & Rahul Rawat
    2. 2. Food insecurity and HIV: What do we know? <ul><li>Food insecurity is associated with: </li></ul><ul><ul><li>HIV transmission </li></ul></ul><ul><ul><li>Access to care and treatment services </li></ul></ul><ul><ul><li>ART adherence </li></ul></ul><ul><ul><li>Immunological/virological outcomes </li></ul></ul><ul><ul><li>Survival </li></ul></ul><ul><li>Complicates AIDS impact mitigation </li></ul>Weiser SD et al 2009; Normen L et al 2005; Weiser SD et al 2008 and other sources RISK IMPACT HIV AIDS Prevention Care & Treatment Mitigation
    3. 3. Rationale for Nutrition Programs <ul><li>High geographic overlap between HIV prevalence, malnutrition, and chronic food insecurity; weight loss is a significant prognostic factor of mortality since the beginning of the AIDS epidemic </li></ul><ul><li>Despite improved access to ART, malnutrition complicates the provision of care in resource limited settings </li></ul><ul><ul><li>low BMI at ART initiation is an independent predictor of early mortality (Zambia, Malawi, Tanzania) </li></ul></ul><ul><li>The proposed benefits of early weight gain serve as the theoretical basis for food supplementation programs </li></ul><ul><li>Limited evidence of impacts of nutrition interventions </li></ul>Source: Zachariah et al (AIDS 2006); Johannessen et al. (BMC Infectious Disease 2008); Koethe et al. (JAIDS 2010)
    4. 4. Nutrition Program Responses <ul><li>HIV services integrating food and nutrition components </li></ul><ul><ul><li>Food by Prescription </li></ul></ul><ul><ul><ul><li>Specialized Food Products (RUFs, FBFs) </li></ul></ul></ul><ul><li>Food Assistance Programs </li></ul><ul><ul><li>Delivery of food baskets (CSB, oil, maize meal, pulses etc.) </li></ul></ul><ul><ul><li>Title II, WFP </li></ul></ul><ul><li>Livelihood Security Programs </li></ul><ul><ul><li>Provision of agricultural inputs and training to promote local food production </li></ul></ul>
    5. 5. Food Insecurity, Undernutrition and HIV: 3 key questions <ul><li>What are the determinants of undernutrition among PLHIVs? </li></ul><ul><ul><li>Do dietary diversity and food insecurity influence nutrition, quality of life and clinical outcomes? </li></ul></ul><ul><li>What is the impact of food based interventions in improving welfare of PLHIVs and their households? </li></ul><ul><li>How can livelihood programs in the context of HIV be improved? </li></ul><ul><li>RENEWAL –TASO Collaboration was designed to answer these key questions </li></ul>
    6. 6. 3 Key Components (2007-2010) <ul><li>Conduct a prospective impact evaluation of a WFP food assistance program </li></ul><ul><li>Using an existing TASO database, create a panel data set to retrospectively evaluate the impact of food assistance </li></ul><ul><li>Conduct operations research (OR) study to understand key challenges in livelihood programming (next presentation) </li></ul>
    7. 7. Study 1: Food Effectiveness Study <ul><li>Objective: To estimate the effectiveness of food support (in the form of a WFP HH food basket) provided to HIV-infected individuals who are not yet on anti-retroviral therapy (ART) </li></ul><ul><li>Quasi-experimental study in 2 TASO program areas </li></ul><ul><ul><li>Gulu (Intervention): 450 HHs receiving a monthly WFP food ration for 12 months </li></ul></ul><ul><ul><li>Soroti (Matched Control): 450 HHs that qualify, but do not receive, WFP food ration </li></ul></ul><ul><ul><li>CD4 count: 200-500 cell/µl </li></ul></ul><ul><li>Baseline: August ’08 - September ‘09 </li></ul><ul><li>Endline: August ’09 – September ‘10 </li></ul>
    8. 8. Outcomes of Interest in Programs <ul><li>Individual </li></ul><ul><li>Disease progression (CD4 count, WHO stage) </li></ul><ul><li>Nutritional status (BMI, MUAC, Hb) </li></ul><ul><li>High risk behavior </li></ul><ul><li>Labor activities </li></ul><ul><li>Quality of life </li></ul><ul><li>Disclosure </li></ul><ul><li>Stigma </li></ul><ul><li>Household </li></ul><ul><li>HH food security </li></ul><ul><li>Dietary diversity </li></ul><ul><li>Child nutritional status (<5 yrs) </li></ul><ul><li>Economic activities and employment </li></ul><ul><li>Asset ownership </li></ul><ul><li>Expenditure (food & non food) </li></ul><ul><li>Agriculture production </li></ul><ul><li>Credit & savings </li></ul>
    9. 9. Emerging Results <ul><li>Previous studies consistently show malnutrition as a strong predictor of mortality </li></ul><ul><li>Determinants of malnutrition among PLHIVs are not well established </li></ul><ul><ul><li>Do HH characteristics like dietary diversity and food insecurity influence nutritional status, independent of disease progression? </li></ul></ul><ul><ul><li>What is pathway through which food security influences nutritional status? </li></ul></ul><ul><li>Are food security and dietary diversity associated with disease severity? </li></ul>
    10. 10. Determinants of Undernutrition <ul><li>Mean BMI: 20.5 (± 2.6) kg/m 2 ; MUAC: 267 (± 28) mm; DDS: 6.3 (± 1.7) food groups </li></ul><ul><li>DD and HH FS are significantly, and independently, associated with nutritional status independent of SES, and disease stage </li></ul>HH Food Insecurity Individual Dietary Diversity Mean BMI values adjusted for CD4 count, sex, HH expenditure, HH asset value district, HH size, education Δ =0.45 kg/m 2 ; p = 0.031 Δ =0.90 kg/m 2 ; p = 0.001 Δ =0.63 kg/m 2 ; p = 0.001
    11. 11. Determinants of Undernutrition <ul><li>HIV-infected individuals living in severely food insecure HH have a 1.9 times greater odds (p<0.001) of being malnourished (BMI<18.5kg/m 2 ) </li></ul><ul><li>HIV-infected individuals living consuming a highly diverse diet (>8 food groups per day) are 50% lower odds (p<0.05) of being malnourished (BMI<18.5kg/m 2 ) compared to those consuming a low diverse diet (<5 food groups per day) </li></ul>
    12. 12. Evaluating Pathways to Undernutrition: Path Analysis Notes: Numbers in parentheses are standard errors. For both Path 1 (Dietary Diversity) and Path 2 (BMI), the model is adjusted for all variables included in regression models presented in Tables 2 and 3. *p<0.05; ** p<0.01 Path and Dependent Outcome Predictor Vairable Direct Effect Indirect Effect Total Effect Path 1: Dietary Diversity Food Insecurity -0.043** (0.011) Path 2: BMI (kg/m 2 ) Dietary Diversity Food Insecurity 0.139* (0.056) -0.062** (0.019) -0.006* (0.057) -0.068* (0.060)
    13. 13. Nutritional Determinants of Disease Severity <ul><li>Predictors of CD4 count <350 cells/uL </li></ul><ul><li>Diet quality, but not HH Food Security is associated with disease severity </li></ul>Model adjusted for age, sex, district, HH expenditure, HH asset value district, HH size, education Category Odds Ratio (p value) Severe HH Food Insecurity 0.95 (0.754) Nutrient Rich Foods (ASF, MN rich fruits and vegetables) 0.84 (0.019) Cereals and Starches 1.16 (0.280) Fats and Oils 1.11 (0.304)
    14. 14. Study 2: Retrospective Evaluation of the TASO database <ul><li>TASO electronic monitoring data system </li></ul><ul><ul><li>patient's intake registration form; medical visit summaries; counseling visit summaries; ART initiation and other drug use; social support services </li></ul></ul><ul><li>Between 2002-2007 TASO had 195,676 registered patients </li></ul><ul><ul><li>Database for analysis had 14,481 patients </li></ul></ul><ul><li>Examined changes over 12 months for patients and how the receipt of FA influences weight gain and disease progression </li></ul><ul><ul><li>Used PSM to match each FA recipient with similar non-FA recipients; uses the outcome of the non-FA recipients as a proxy for the outcome of the FA recipients if they had not received FA </li></ul></ul>Source: Rawat et al. (BMC Public Health 2010)
    15. 15. Impact of Food Assistance on Weight Gain ** significant at 1% ; *significant at 5% ; + significant at 10% a Absolute value of t-statistics on ATT, in parentheses, are based on bootstrapped standard errors Source: Rawat et al. (BMC Public Health 2010) Change in Weight (kg) Food assistance Recipients (n) Matched Controls (n) ATT a (absolute value of t-statistic) Overall 3202 11069 0.36 (3.19)** Conditional estimates Without ART 2783 9661 0.48 (2.14)* With ART 546 1120 0.17 (1.5) Baseline WHO stage 1 327 1479 -0.2 (0.55) Baseline WHO stage 2 2329 7318 0.26 (2.3)* Baseline WHO stage 3 615 1807 0.2 (1.8) + Baseline WHO stage 4 58 129 1.9 (1.9) +
    16. 16. Impact of Food Assistance on Weight Gain ** significant at 1% ; *significant at 5% ; + significant at 10% a Absolute value of t-statistics on ATT, in parentheses, are based on bootstrapped standard errors Source: Rawat et al. (BMC Public Health 2010) Change in Weight (kg) Food assistance Recipients (n) Matched Controls (n) ATT a (absolute value of t-statistic) Overall 3202 11069 0.36 (3.19)** Conditional estimates Without ART 2783 9661 0.48 (2.14)* With ART 546 1120 0.17 (1.5) Baseline WHO stage 1 327 1479 -0.2 (0.55) Baseline WHO stage 2 2329 7318 0.26 (2.3)* Baseline WHO stage 3 615 1807 0.2 (1.8) + Baseline WHO stage 4 58 129 1.9 (1.9) +
    17. 17. Preliminary Conclusions <ul><li>Ensuring diet quality, in addition to food access, should be a focus for programs </li></ul><ul><ul><li>HH food insecurity and dietary diversity are independent predictors of nutritional status </li></ul></ul><ul><ul><li>Diet quality, and not food insecurity, is associated with disease severity </li></ul></ul><ul><li>There is preliminary evidence of the impact of food assistance on weight gain </li></ul><ul><ul><li>Impact on disease progression needs further investigation </li></ul></ul><ul><li>Stay tuned for prospective impact evaluation results </li></ul>
    18. 18. Looking Ahead: Knowledge Gaps to Improve Programs <ul><li>Composition of nutritional support, and package of services (food, health and other) </li></ul><ul><li>Timing of support </li></ul><ul><ul><ul><li>pre ART vs. post ART </li></ul></ul></ul><ul><ul><ul><li>role in delaying progression </li></ul></ul></ul><ul><li>Duration of interventions & exit criteria </li></ul><ul><li>Health system capacity to integrate HIV and nutrition services </li></ul><ul><ul><li>Delivery systems </li></ul></ul><ul><ul><li>Referral systems </li></ul></ul><ul><li>Alternate food security and nutrition programs </li></ul><ul><ul><li>Design and implementation of programs </li></ul></ul><ul><ul><li>Impacts (nutrition, health, quality of life and other socioeconomic outcomes) </li></ul></ul><ul><li>Cost-effectiveness of different interventions </li></ul>
    19. 19. Key Publications (2007-date) <ul><li>HIV and Livelihood Programming </li></ul><ul><li>Kadiyala S, Rawat R, Roopnaraine T, Babirye F, Ochai R (2009). Applying a Program Theory Framework to Improve Livelihood Interventions Integrated with HIV Care and Treatment Programs . Journal of Development Effectiveness 2009 ; 1 (4): 470 -491 </li></ul><ul><li>Roopnaraine T, Rawat R, Babirye F, Ochai R, Kadiyala (2010). ‘The Group’ in Integrated HIV and Food Security Programming: Opportunity or Challenge? (Submitted to AIDS Care) </li></ul><ul><li>HIV and Food Assistance Programming </li></ul><ul><li>Rawat R, Kadiyala S, McNamara P. 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: 316 </li></ul><ul><li>Kadiyala S & Rawat R. Determinants of undernutrition among HIV infected individuals accessing care services in Uganda (manuscript in preparation; to be submitted Nov. 15) </li></ul><ul><li>Rawat R & Kadiyala S. Food quality rather than food access independently predicts HIV disease severity in Uganda (manuscript in preparation) </li></ul><ul><li>HIV and Food Security Reviews </li></ul><ul><li>Anema A Vogenthaler N, Frongillo EA, Kadiyala S, Weiser SD (2009). Food Insecurity and HIV/AIDS:Current Knowledge, Gaps, and Research Priorities. Current HIV/AIDS Reports 2009, 6:224–231 </li></ul><ul><li>Frega R, Duffy F, Rawat R, Grede N. Food Insecurity in the Context of HIV and AIDS: A Framework for a New Era of Programming . Food and Nutrition Bulletin (In Press, to be published in December 2010) </li></ul>

    ×