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Published in: AIDS and Behavior 12/2017

01-12-2017 | Original Paper

The Impact of Food Assistance on Dietary Diversity and Food Consumption among People Living with HIV/AIDS

Authors: Nyasha Tirivayi, Wim Groot

Published in: AIDS and Behavior | Issue 12/2017

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Abstract

Little is known about the outcomes of food assistance targeted to food insecure people living with HIV/AIDS. Using primary data from Zambia, we estimated the impact of food assistance on the dietary diversity and consumption expenditures of households with HIV infected members receiving antiretroviral therapy. Propensity score matching estimates show that food assistance increased dietary diversity by 9.8 points (23%) mainly through the consumption of food items provided in the ration. Food assistance recipients were 20% points more likely to have acceptable food consumption and 15% points less likely to have poor food consumption than non-recipients. Food assistance also increased food consumption expenditures but had no significant impact on food purchases and total consumption expenditures. Overall, our findings demonstrate that food assistance can be an effective instrument for improving diets and enhancing the food security of people living with HIV/AIDS.
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Footnotes
1
We hypothesized that 25% of the intervention group would have poor dietary diversity compared to 45% in the comparison group.
 
Literature
1.
go back to reference Weiser SD, Tsai AC, Gupta R, Frongillo EA, Kawuma A, Senkungu J, Hunt PW, Emenyonu NI, Mattson JE, Martin JN, Bangsberg DR. Food insecurity is associated with morbidity and patterns of healthcare utilization among HIV-infected individuals in a resource-poor setting. AIDS. 2012;26:67–75.CrossRefPubMedPubMedCentral Weiser SD, Tsai AC, Gupta R, Frongillo EA, Kawuma A, Senkungu J, Hunt PW, Emenyonu NI, Mattson JE, Martin JN, Bangsberg DR. Food insecurity is associated with morbidity and patterns of healthcare utilization among HIV-infected individuals in a resource-poor setting. AIDS. 2012;26:67–75.CrossRefPubMedPubMedCentral
2.
go back to reference Weiser SD, Young SL, Cohen CR, Kushel MB, Tsai AC, Tien PC, Hatcher AM, Frongillo EA, Bangsberg DR. Conceptual framework for understanding the bidirectional links between food insecurity and HIV/AIDS. Am J Clin Nutr. 2011;94:1729S–39S.CrossRefPubMedPubMedCentral Weiser SD, Young SL, Cohen CR, Kushel MB, Tsai AC, Tien PC, Hatcher AM, Frongillo EA, Bangsberg DR. Conceptual framework for understanding the bidirectional links between food insecurity and HIV/AIDS. Am J Clin Nutr. 2011;94:1729S–39S.CrossRefPubMedPubMedCentral
3.
go back to reference Wang EA, McGinnis KA, Fiellin DA, Goulet JL, Bryant K, Gibert CL, Leaf DA, Mattocks K, Sullivan LE, Vogenthaler N, Justice AC. Food insecurity is associated with poor virologic response among HIV-infected patients receiving antiretroviral medications. J Gen Intern Med. 2011;26:1012–8.CrossRefPubMedPubMedCentral Wang EA, McGinnis KA, Fiellin DA, Goulet JL, Bryant K, Gibert CL, Leaf DA, Mattocks K, Sullivan LE, Vogenthaler N, Justice AC. Food insecurity is associated with poor virologic response among HIV-infected patients receiving antiretroviral medications. J Gen Intern Med. 2011;26:1012–8.CrossRefPubMedPubMedCentral
4.
go back to reference de Pee S, Semba RD. Role of nutrition in HIV infection: review of evidence for more effective programming in resource-limited settings. Food Nutr Bull. 2010;31:S313–44.CrossRef de Pee S, Semba RD. Role of nutrition in HIV infection: review of evidence for more effective programming in resource-limited settings. Food Nutr Bull. 2010;31:S313–44.CrossRef
5.
go back to reference Johannessen A, Naman E, Ngowi BJ, Sandvik L, Matee MI, Aglen HE, Gundersen SG, Bruun JN. Predictors of mortality in HIV-infected patients starting antiretroviral therapy in a rural hospital in Tanzania. BMC Infect Dis. 2008;8(52) Johannessen A, Naman E, Ngowi BJ, Sandvik L, Matee MI, Aglen HE, Gundersen SG, Bruun JN. Predictors of mortality in HIV-infected patients starting antiretroviral therapy in a rural hospital in Tanzania. BMC Infect Dis. 2008;8(52)
6.
go back to reference Tirivayi N, Groot W. Health and welfare effects of integrating AIDS treatment with food assistance in resource constrained settings: a systematic review of theory and evidence. Soc Sci Med. 2011;73:685–92.CrossRefPubMed Tirivayi N, Groot W. Health and welfare effects of integrating AIDS treatment with food assistance in resource constrained settings: a systematic review of theory and evidence. Soc Sci Med. 2011;73:685–92.CrossRefPubMed
7.
go back to reference Byron E, Gillespie S, Nangami M. Integrating nutrition security with treatment of people living with HIV: lessons from Kenya. Food Nutr Bull. 2008;29(2):87–97.CrossRefPubMed Byron E, Gillespie S, Nangami M. Integrating nutrition security with treatment of people living with HIV: lessons from Kenya. Food Nutr Bull. 2008;29(2):87–97.CrossRefPubMed
8.
go back to reference Tirivayi N, Koethe JR, Groot W. Clinic-based food assistance is associated with increased medication adherence among HIV-infected adults on long-term antiretroviral therapy in Zambia. J AIDS Clin Res. 2012;3:171–8.CrossRefPubMedPubMedCentral Tirivayi N, Koethe JR, Groot W. Clinic-based food assistance is associated with increased medication adherence among HIV-infected adults on long-term antiretroviral therapy in Zambia. J AIDS Clin Res. 2012;3:171–8.CrossRefPubMedPubMedCentral
9.
go back to reference Cantrell RA, Sinkala M, Megazinni K, Lawson-Marriott S, Washington S, Chi B, Tambatamba-Chapula B, Levy J, Stringer E, Mulenga L, Stringer J. A Pilot Study of Food Supplementation to Improve Adherence to Antiretroviral Therapy among Food-Insecure Adults in Lusaka, Zambia. JAIDS J Acquir Immune Defic Syndr. 2008;49(2):190–5.CrossRefPubMed Cantrell RA, Sinkala M, Megazinni K, Lawson-Marriott S, Washington S, Chi B, Tambatamba-Chapula B, Levy J, Stringer E, Mulenga L, Stringer J. A Pilot Study of Food Supplementation to Improve Adherence to Antiretroviral Therapy among Food-Insecure Adults in Lusaka, Zambia. JAIDS J Acquir Immune Defic Syndr. 2008;49(2):190–5.CrossRefPubMed
10.
go back to reference 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;10:316–23.CrossRefPubMedPubMedCentral 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;10:316–23.CrossRefPubMedPubMedCentral
11.
go back to reference Rawat R, Faust E, Maluccio JA, Kadiyala S. The impact of a food assistance program on nutritional status, disease progression, and food security among people living with HIV in Uganda. JAIDS J Acquir Immune Defic Syndr. 2014;66(1):e15–22.CrossRefPubMed Rawat R, Faust E, Maluccio JA, Kadiyala S. The impact of a food assistance program on nutritional status, disease progression, and food security among people living with HIV in Uganda. JAIDS J Acquir Immune Defic Syndr. 2014;66(1):e15–22.CrossRefPubMed
12.
go back to reference Jones AD, Ngure FM, Pelto G, Young SL. What are we assessing when we measure food security? A compendium and review of current metrics. Adv Nutr. 2013;4(5):481–505.CrossRefPubMedPubMedCentral Jones AD, Ngure FM, Pelto G, Young SL. What are we assessing when we measure food security? A compendium and review of current metrics. Adv Nutr. 2013;4(5):481–505.CrossRefPubMedPubMedCentral
13.
go back to reference Kennedy GL, Pedro MR, Seghieri C, Nantel G, Brouwer I. Dietary diversity score is a useful indicator of micronutrient intake in non-breast-feeding Filipino children. J Nutr. 2007;137(2):472–7.PubMed Kennedy GL, Pedro MR, Seghieri C, Nantel G, Brouwer I. Dietary diversity score is a useful indicator of micronutrient intake in non-breast-feeding Filipino children. J Nutr. 2007;137(2):472–7.PubMed
14.
go back to reference Steyn N, Nel J, Nantel G, Kennedy G, Labadarios D. Food variety and dietary diversity scores in children: are they good indicators of dietary adequacy? Public Health Nutr. 2006;9:644–50.CrossRefPubMed Steyn N, Nel J, Nantel G, Kennedy G, Labadarios D. Food variety and dietary diversity scores in children: are they good indicators of dietary adequacy? Public Health Nutr. 2006;9:644–50.CrossRefPubMed
15.
go back to reference Arimond M, Ruel MT. Dietary diversity is associated with child nutritional status: evidence from 11 demographic and health surveys. J Nutr. 2004;134(10):2579–85.PubMed Arimond M, Ruel MT. Dietary diversity is associated with child nutritional status: evidence from 11 demographic and health surveys. J Nutr. 2004;134(10):2579–85.PubMed
16.
go back to reference Rawat R, McCoy SI, Kadiyala S. Poor diet quality is associated with low CD4 count and anemia and predicts mortality among antiretroviral therapy–naive HIV-positive adults in Uganda. JAIDS J Acquir Immune Defic Syndr. 2013;12:246–53.CrossRef Rawat R, McCoy SI, Kadiyala S. Poor diet quality is associated with low CD4 count and anemia and predicts mortality among antiretroviral therapy–naive HIV-positive adults in Uganda. JAIDS J Acquir Immune Defic Syndr. 2013;12:246–53.CrossRef
18.
go back to reference Wiesmann D, Bassett L, Benson T, Hoddinott J. Validation of the World Food Program’s food consumption score and alternative in-dicators of household food security. 2009. IFPRI Discussion Paper 00870. Washington, DC: IFPRI. Wiesmann D, Bassett L, Benson T, Hoddinott J. Validation of the World Food Program’s food consumption score and alternative in-dicators of household food security. 2009. IFPRI Discussion Paper 00870. Washington, DC: IFPRI.
19.
go back to reference World Food Program (WFP). Food consumption analysis: calculation and use of the food consumption score in food consumption and food security analysis. Technical Guidance Sheet. Rome: World Food Program; 2007a. World Food Program (WFP). Food consumption analysis: calculation and use of the food consumption score in food consumption and food security analysis. Technical Guidance Sheet. Rome: World Food Program; 2007a.
20.
go back to reference Gilligan DO, Margolies A, Quiñones E, Roy S. Impact evaluation of cash and food transfers at early childhood development centers in Karamoja, Uganda. Washington, DC: IFPRI; 2013. Gilligan DO, Margolies A, Quiñones E, Roy S. Impact evaluation of cash and food transfers at early childhood development centers in Karamoja, Uganda. Washington, DC: IFPRI; 2013.
21.
go back to reference Heckman JJ, Ichimura H, Todd P. Matching as an econometric evaluation estimator. Rev Econ Stud. 1998;65(2):261–94.CrossRef Heckman JJ, Ichimura H, Todd P. Matching as an econometric evaluation estimator. Rev Econ Stud. 1998;65(2):261–94.CrossRef
22.
go back to reference Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70(1):41–5.CrossRef Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70(1):41–5.CrossRef
23.
go back to reference Caliendo M, Kopeinig S. Some practical guidance for the implementation of propensity score matching. J Econ Surv. 2008;22(1):31–72.CrossRef Caliendo M, Kopeinig S. Some practical guidance for the implementation of propensity score matching. J Econ Surv. 2008;22(1):31–72.CrossRef
24.
go back to reference Leuven E, Sianesi B. PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Version 3.1.5. 2003 Leuven E, Sianesi B. PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Version 3.1.5. 2003
25.
go back to reference Smith J, Todd P. Does matching overcome LaLonde’s critique of nonexperimental estimators? J Econom. 2005;125(1–2):305–53.CrossRef Smith J, Todd P. Does matching overcome LaLonde’s critique of nonexperimental estimators? J Econom. 2005;125(1–2):305–53.CrossRef
26.
go back to reference Dehejia RH, Wahba S. Propensity score matching methods for nonexperimental causal studies. Rev Econ Stat. 2000;84(1):151–61.CrossRef Dehejia RH, Wahba S. Propensity score matching methods for nonexperimental causal studies. Rev Econ Stat. 2000;84(1):151–61.CrossRef
27.
go back to reference Sianesi B. An evaluation of the Swedish system of active labor market programs in the 1990s. Rev Econ Stat. 2004;86(1):133–55.CrossRef Sianesi B. An evaluation of the Swedish system of active labor market programs in the 1990s. Rev Econ Stat. 2004;86(1):133–55.CrossRef
28.
go back to reference Rosenbaum PR, Rubin DB. Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. Am Stat. 1985;39:33–8. Rosenbaum PR, Rubin DB. Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. Am Stat. 1985;39:33–8.
29.
go back to reference DiPrete TA, Gangl M. Assessing bias in the estimation of causal effects: rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments. Sociol Methodol. 2004;34(1):271–310.CrossRef DiPrete TA, Gangl M. Assessing bias in the estimation of causal effects: rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments. Sociol Methodol. 2004;34(1):271–310.CrossRef
30.
go back to reference Becker SO, Caliendo M. Sensitivity analysis for average treatment effect. Stata J. 2007;7(1):71–83. Becker SO, Caliendo M. Sensitivity analysis for average treatment effect. Stata J. 2007;7(1):71–83.
31.
go back to reference Caliendo M, Hujer R, Thomsen S. The employment effects of job creation schemes in Germany—a microeconometric evaluation. In: Millimet DL, Smith JA, Vytlacil E, editors. Modeling and evaluating treatment effects in econometrics, advances in econometrics, vol. 21. Amsterdam: Elsevier; 2008. p. 381–428. Caliendo M, Hujer R, Thomsen S. The employment effects of job creation schemes in Germany—a microeconometric evaluation. In: Millimet DL, Smith JA, Vytlacil E, editors. Modeling and evaluating treatment effects in econometrics, advances in econometrics, vol. 21. Amsterdam: Elsevier; 2008. p. 381–428.
33.
go back to reference Hidrobo MJ, Hoddinott J, Peterman A, Margolies A, Moreira V. Cash, food, or vouchers? evidence from a randomized experiment in northern Ecuador. J Dev Econ. 2014;107:144–56.CrossRef Hidrobo MJ, Hoddinott J, Peterman A, Margolies A, Moreira V. Cash, food, or vouchers? evidence from a randomized experiment in northern Ecuador. J Dev Econ. 2014;107:144–56.CrossRef
34.
go back to reference Aberman NL, Rawat R, Drimie S, Claros JM, Kadiyala S. Food security and nutrition interventions in response to the aids epidemic: assessing global action and evidence. AIDS Behav. 2014;18(5):554–65.CrossRef Aberman NL, Rawat R, Drimie S, Claros JM, Kadiyala S. Food security and nutrition interventions in response to the aids epidemic: assessing global action and evidence. AIDS Behav. 2014;18(5):554–65.CrossRef
35.
go back to reference World Food Program (WFP). HIV and AIDS and OVC beneficiary profiles: vulnerability analysis from six countries in Southern Africa. Rome: World Food Program; 2007b. World Food Program (WFP). HIV and AIDS and OVC beneficiary profiles: vulnerability analysis from six countries in Southern Africa. Rome: World Food Program; 2007b.
Metadata
Title
The Impact of Food Assistance on Dietary Diversity and Food Consumption among People Living with HIV/AIDS
Authors
Nyasha Tirivayi
Wim Groot
Publication date
01-12-2017
Publisher
Springer US
Published in
AIDS and Behavior / Issue 12/2017
Print ISSN: 1090-7165
Electronic ISSN: 1573-3254
DOI
https://doi.org/10.1007/s10461-016-1646-9

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