Agricultural Intervention for Food Security and HIV Health Outcomes in Kenya

HIV Clinical Trial

— Shamba R01  

Official title:

Agricultural Intervention for Food Security and HIV Health Outcomes in Kenya

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT02815579
• Other study ID #: P0503135
• Secondary ID: R01MH107330-01
• Status: Completed
• Phase: N/A
• Start date: June 2016
• Est. completion date: December 2019

Study information

• Verified date: April 2024
• Source: University of California, San Francisco
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The purpose of this study is to determine whether this multisectoral agricultural and microcredit loan intervention improves food security, prevent antiretroviral treatment failure, and reduce co-morbidities among people living with HIV/AIDS.

Description:

Despite major advances in care and treatment for those living with HIV, morbidity and mortality among people living with HIV/AIDS (PLHIV) remains unacceptably high in sub-Saharan Africa (SSA), largely due to the parallel challenges of poverty and food insecurity.[1] In the Nyanza Region of Kenya, 15.1% of the adult population is infected by HIV,[2] and over 50% of the rural population is food insecure, primarily due to unpredictable rainfall and limited irrigation.[3,4] The investigators have previously shown that food insecurity delays antiretroviral therapy (ART) initiation, reduces ART adherence, contributes to worse immunologic and virologic outcomes, and increases morbidity and mortality among PLHIV.[5-16] There has been increasing international recognition that improved food security and reduced poverty are essential components for a successful global response to the HIV epidemic.[17-21] Yet, to date few studies have systematically evaluated the impacts of sustainable food security interventions on health, economic, and behavioral outcomes among PLHIV. Agricultural interventions, which have potential to raise income and bolster food security, are an important but understudied route through which to sustainably improve nutritional and HIV outcomes in SSA, including Kenya where agriculture accounts for > 75% of the total workforce, and 51% of the gross domestic product.[22]

Building on the investigators successful completion of the pilot intervention trial in Kenya and the investigators collective experience studying structural barriers to HIV care in SSA, the investigators plan to test the hypothesis that a multisectoral agricultural and microcredit loan intervention will improve food security, prevent ART treatment failure, and reduce co-morbidities among PLHIV. The investigators' intervention was co-developed with KickStart, a prominent non-governmental organization (NGO) based in SSA that has introduced a human-powered pump, enabling farmers to grow high yield crops year-round. This technology has reduced food insecurity and poverty for 800,000 users in 22 countries in the subcontinent since 1991.[23] The investigators' intervention includes: a) a loan (~$175) from a well-established Kenyan bank for purchasing agricultural implements and commodities; b) agricultural implements to be purchased with the loan including the KickStart treadle pump, seeds, fertilizers and pesticides; and c) education in financial management and sustainable farming practices occurring in the setting of patient support groups. This study is a cluster randomized controlled trial (RCT) of this intervention with the following specific aims:

Aim 1: To determine the impact of a multisectoral agricultural intervention among HIV-infected farmers on ART on HIV clinical outcomes. The investigators hypothesize that the intervention will lead to improved viral load suppression (primary outcome) and changes in CD4 cell count, physical health status, WHO stage III/IV disease, and hospitalizations (secondary outcomes) in the intervention arm compared to the control arm.

Aim 2: To understand the pathways through which the multisectoral intervention may improve HIV health outcomes. Using the investigator's theoretical model,[1,24] the investigators hypothesize that the intervention will improve food security and household wealth, which in turn will contribute to improved outcomes through nutritional (improved nutritional status measured with Body Mass Index), behavioral (improved ART adherence, and retention in care), and mental health (improved mental health/less depression, improved empowerment) pathways (secondary outcomes).

Aim 3: To determine the cost-effectiveness of the intervention and obtain the information necessary to inform scale-up in Kenya and similar settings in SSA. The investigators will quantify the cost per disability-adjusted life year averted, and identify lessons to inform successful scale-up.

To accomplish Aims 1 & 2, the investigators will randomize 8 matched pairs of health facilities in the Nyanza Region in a 1:1 ratio to the intervention and control arms, and enroll 44 participants per facility (total n=704). All participants will be followed for 2 years. Impacts of the investigator's intervention on primary health outcomes and mediators will be investigated to provide definitive data of direct and indirect intervention effects. To accomplish Aim 3, the investigators will: a) conduct a cost-effectiveness analysis; b) identify the characteristics of individuals most likely to benefit from the intervention (e.g., gender, educational attainment, family size, wealth, risk tolerance, and entrepreneurial ability); and c) perform a mixed-methods process evaluation with study participants, staff, and various stakeholders to determine what worked and did not work to guide future scale-up efforts of the intervention.

The investigator's ultimate goal is to develop and test an intervention to reverse the cycle of food insecurity and HIV/AIDS morbidity and mortality in SSA.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 746
• Est. completion date: December 2019
• Est. primary completion date: December 2019
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 60 Years

Eligibility

Inclusion Criteria:

• HIV-infected adults

• Currently receiving ART

• Belong to a patient support group or demonstrate willingness to join a support group

• Agree to save the down payment (~$10) required for the microcredit loan

• Have evidence of moderate to severe food insecurity based on the Household Food Insecurity Access Scale (HFIAS), and/or malnutrition (BMI<18.5) based on FACES medical records during the year preceding recruitment

• Have access to farming land and available surface water in the form of lakes, rivers, ponds and shallow wells

Exclusion Criteria:

• People who do not speak Dholuo, Swahili, or English

• Inadequate cognitive and/or hearing capacity to complete planned study procedures, at the discretion of the research assistant

Related Conditions & MeSH terms

• HIV

Intervention

Other:
• Shamba Maisha Intervention
A) A loan (~$175) B) Agricultural implements to be purchased with the loan C) Education in financial management and sustainable farming practices

Locations

Country	Name	City	State
Kenya	Hongo Ogosa	Kisumu
Kenya	Kisumu District Hospital	Kisumu
Kenya	Lumumba	Kisumu
Kenya	Nyangande	Kisumu
Kenya	Pandiperi	Kisumu
Kenya	Railways	Kisumu
Kenya	Osingo	Migori
Kenya	Suna Ragana	Migori
Kenya	Muhuru Bay	Nyatike	Migori
Kenya	Sori Lakeside	Nyatike	Migori
Kenya	Minyenya	Rongo	Migori
Kenya	Ngode	Rongo	Migori
Kenya	Oyani	Rongo	Migori
Kenya	Kitare	Suba	Homa Bay
Kenya	Sindo	Suba	Homa Bay
Kenya	Nyamasare	Uriri	Migori

Sponsors (6)

Lead Sponsor	Collaborator
University of California, San Francisco	Kenya Medical Research Institute, National Institute of Mental Health (NIMH), University of Connecticut, University of Pennsylvania, University of South Carolina

Country where clinical trial is conducted

Kenya, 

References & Publications (24)

Byron E, Gillespie S, Nangami M. Integrating nutrition security with treatment of people living with HIV: lessons from Kenya. Food Nutr Bull. 2008 Jun;29(2):87-97. doi: 10.1177/156482650802900202. — View Citation

KickStart. KickStart Impact. http://www.kickstart.org/what-we-do/impact/. Accessed July 11, 2014.

Mamlin J, Kimaiyo S, Lewis S, Tadayo H, Jerop FK, Gichunge C, Petersen T, Yih Y, Braitstein P, Einterz R. Integrating nutrition support for food-insecure patients and their dependents into an HIV care and treatment program in Western Kenya. Am J Public Health. 2009 Feb;99(2):215-21. doi: 10.2105/AJPH.2008.137174. Epub 2008 Dec 4. — View Citation

McMahon JH, Wanke CA, Elliott JH, Skinner S, Tang AM. Repeated assessments of food security predict CD4 change in the setting of antiretroviral therapy. J Acquir Immune Defic Syndr. 2011 Sep 1;58(1):60-3. doi: 10.1097/QAI.0b013e318227f8dd. — View Citation

Musumari PM, Feldman MD, Techasrivichien T, Wouters E, Ono-Kihara M, Kihara M. "If I have nothing to eat, I get angry and push the pills bottle away from me": A qualitative study of patient determinants of adherence to antiretroviral therapy in the Democratic Republic of Congo. AIDS Care. 2013;25(10):1271-7. doi: 10.1080/09540121.2013.764391. Epub 2013 Feb 6. — View Citation

Musumari PM, Wouters E, Kayembe PK, Kiumbu Nzita M, Mbikayi SM, Suguimoto SP, Techasrivichien T, Lukhele BW, El-Saaidi C, Piot P, Ono-Kihara M, Kihara M. Food insecurity is associated with increased risk of non-adherence to antiretroviral therapy among HIV-infected adults in the Democratic Republic of Congo: a cross-sectional study. PLoS One. 2014 Jan 15;9(1):e85327. doi: 10.1371/journal.pone.0085327. eCollection 2014. — View Citation

Nagata JM, Magerenge RO, Young SL, Oguta JO, Weiser SD, Cohen CR. Social determinants, lived experiences, and consequences of household food insecurity among persons living with HIV/AIDS on the shore of Lake Victoria, Kenya. AIDS Care. 2012;24(6):728-36. doi: 10.1080/09540121.2011.630358. Epub 2011 Dec 7. — View Citation

National AIDS and STI Control Programme, Ministry of Health, Kenya. September 2013. Kenya AIDS Indicator Survey 2012: Preliminary Report. Nairobi, Kenya

Place F, Adato M, Hebinck P. Understanding rural poverty and investment in agriculture: an assessment of integrated quantitative and qualitative research in western Kenya. World Dev. 2007;35(2):312-325.

Sasaki Y, Kakimoto K, Dube C, Sikazwe I, Moyo C, Syakantu G, Komada K, Miyano S, Ishikawa N, Kita K, Kai I. Adherence to antiretroviral therapy (ART) during the early months of treatment in rural Zambia: influence of demographic characteristics and social surroundings of patients. Ann Clin Microbiol Antimicrob. 2012 Dec 28;11:34. doi: 10.1186/1476-0711-11-34. — View Citation

Stoorvogel J, Smaling E. Assessment of soil nutrient depletion in sub-Saharan Africa: 1983-2000. Report No. 28, Vols. I-IV. Wageningin, Netherlands: Winand Staring Center; 1990.

The World Bank. HIV/AIDS, Nutrition, and Food Security: What we can do. Washington DC2007.

UNAIDS. Report on the global AIDS epidemic. Geneva: Joint United Nations Programme on HIV/AIDS;2008.

USAID. Feed the Future Program, country profile for Kenya. http://www.feedthefuture.gov/country/kenya. Accessed August 4, 2014.

Wang EA, McGinnis KA, Fiellin DA, Goulet JL, Bryant K, Gibert CL, Leaf DA, Mattocks K, Sullivan LE, Vogenthaler N, Justice AC; VACS Project Team. Food insecurity is associated with poor virologic response among HIV-infected patients receiving antiretroviral medications. J Gen Intern Med. 2011 Sep;26(9):1012-8. doi: 10.1007/s11606-011-1723-8. Epub 2011 May 15. — View Citation

Weiser S, Fernandes K, Anema A, et al. Food insecurity as a barrier to antiretroviral therapy (ART) adherence among HIV-infected individuals in British Columbia. 5th IAS Conference on HIV Pathogenesis, Treatment and Prevention. Cape Town, South Africa2009.

Weiser S, Palar K, Hatcher A, S. Y, Frongillo EA, Laraia BA. Food insecurity and health: A Conceptual Framework. In: Ivers L, ed. Food Insecurity and Public Health. Boston, MA: CRC Press; 2014.

Weiser SD, Fernandes KA, Brandson EK, Lima VD, Anema A, Bangsberg DR, Montaner JS, Hogg RS. The association between food insecurity and mortality among HIV-infected individuals on HAART. J Acquir Immune Defic Syndr. 2009 Nov 1;52(3):342-9. doi: 10.1097/QAI.0b013e3181b627c2. — View Citation

Weiser SD, Gupta R, Tsai AC, Frongillo EA, Grede N, Kumbakumba E, Kawuma A, Hunt PW, Martin JN, Bangsberg DR. Changes in food insecurity, nutritional status, and physical health status after antiretroviral therapy initiation in rural Uganda. J Acquir Immune Defic Syndr. 2012 Oct 1;61(2):179-86. doi: 10.1097/QAI.0b013e318261f064. — View Citation

Weiser SD, Palar K, Frongillo EA, Tsai AC, Kumbakumba E, Depee S, Hunt PW, Ragland K, Martin J, Bangsberg DR. Longitudinal assessment of associations between food insecurity, antiretroviral adherence and HIV treatment outcomes in rural Uganda. AIDS. 2014 Jan 2;28(1):115-20. doi: 10.1097/01.aids.0000433238.93986.35. — View Citation

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 Jan 2;26(1):67-75. doi: 10.1097/QAD.0b013e32834cad37. — View Citation

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 Dec;94(6):1729S-1739S. doi: 10.3945/ajcn.111.012070. Epub 2011 Nov 16. — View Citation

World Health Organization. HIV, food security, and nutrition: World Food Program, UNAIDS;2008.

Young S, Wheeler AC, McCoy SI, Weiser SD. A review of the role of food insecurity in adherence to care and treatment among adult and pediatric populations living with HIV and AIDS. AIDS Behav. 2014 Oct;18 Suppl 5(0 5):S505-15. doi: 10.1007/s10461-013-0547-4. — View Citation

* Note: There are 24 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Change in Proportion of Viral Load Suppression (<=200 Copies/mL)	The outcome was the change from baseline to the end of follow-up (2 years) in the proportion of participants in viral load suppression (=200 copies/mL) compared between study groups using difference-in-differences analyses.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e., Linear Trend) in Proportion of Absolute CD4 Count <=500 Cells/mm^3	The outcome was the change (i.e., linear trend) from baseline to the end of follow-up (2 years) of the proportion of participants with a CD4 cell count <=500 cells/mm^3, compared between study groups using difference-in-differences analyses.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e. Linear Trend) in Mean Physical Health Status	The outcome was the change (i.e. linear trend) from baseline to the end of follow-up (2 years) of the mean physical health score compared between study groups using the differences-in-differences analyses. We used the Medical Outcomes Study HIV Health Survey (MOS-HIV), a tool used to assess health-related quality of life that has been validated in resource-limited settings. Scores standardized to a range of 0 to 100. Higher scores mean a better outcome.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e., Linear Trend) in the Proportion of Participants With AIDS-Defining Condition	The outcome was the change (i.e., linear trend) from baseline to the end of follow-up (2 years) of the proportion of participants with an AIDS-defining condition, compared between study groups using difference-in-differences analyses. AIDS-defining conditions including HIV-related illnesses included in the Centers for Disease Control and Prevention's (CDC) list of diagnostic criteria for AIDS. AIDS-defining conditions include opportunistic infections and cancers that are life-threatening in a person with HIV.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e., Linear Trend) in the Proportion of Participants Who Were Hospitalized in the Previous 6 Months	The outcome was the change (i.e. linear trend) from baseline to end of follow-up (2 years) of the proportion of participants hospitalized in the previous 6 months (yes/no), compared between study groups using difference-in-differences analyses.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e. Linear Trend) in the Mean Score of Food Insecurity Score	The outcome was the change (i.e. linear trend) from baseline to the end of follow-up (2 years) of the mean household food insecurity score, compared between study groups using difference-in-differences analyses.; using the Household Food Insecurity Access Scale (HFIAS). The HFIAS is a tool to assess household food insecurity (access). The scale scores range from 0 to 27, with higher scores indicating greater food insecurity.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e. Linear Trend) in Mean Nutritional Status (Represented by Body Mass Index (BMI))	The outcome was the change (i.e. linear trend) from baseline to the end of follow-up (2 years) of the mean body mass index (BMI) compared between study grouops using the differences-in-differences analyses.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e. Linear Trend) in Mean Self-reported Adherence to Antiretroviral Therapy	The outcome was the change (i.e. linear trend) from baseline to the end of follow-up (2 years) of the mean self-reported adherence to antiretroviral therapy compared between study groups using the differences-in-differences analyses.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e. Linear Trend) in Mean Self-confidence Score	The outcome was the change (i.e. linear tend) from baseline to the end of follow-up (2 years) in the mean self-confidence score, compared between study groups using difference-in-differences analyses. Self-confidence is measured using the three-item Power Within scale, which has a range of 3 to 9 points where lower scores indicate greater self-confidence.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e. Linear Trend) in Proportion of Probable Depression	The outcome was the change (i.e. linear trend) from baseline to the end of follow-up (2 years) in the proportion with probable depression using the Hopkins Symptom Check-list for Depression, compared between study groups using difference-in-differences analyses.	Baseline and endline (2 years after enrollment)
Secondary	Change (i.e. Linear Trend) in the Mean Internalized Stigma Score	The outcome was the change (i.e. linear trend) from baseline to the end of follow-up (2 years) in the mean internalized stigma score compared between study groups using the differences-in-differences analyses. Internalized HIV stigma arises when someone has accepted and endorsed the negative attitudes towards her/himself due to their HIV status. The internalized HIV stigma sub-scale consisted of six items asking respondents to agree with statements related to how they feel about being HIV positive, such as "having HIV makes me feel like I'm a bad person" and "I feel ashamed of having HIV." Response options ranged from 1 "strongly disagree" to 5 "strongly agree." During the analysis phase, the composite scores of each stigma sub-scale were rescaled to a row average of 1-5, with higher scores indicating greater stigma.	Baseline and endline (2 years after enrollment)