IFPRI Gender Methods Seminar, May 28, 2015: Exploring Food Security and Mental Health in Upper West Ghana Through Empowerment
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Jessica Ham is a bio-cultural anthropologist and PhD candidate at the University of Georgia who was selected in 2012 to receive a Women’s Empowerment in Agriculture (WEAI) Ph.D. dissertation research fellowship. As a bio-cultural anthropologist, she seeks to understand how our social and economic worlds influence human health and biology. Specifically, her dissertation research looks at how food insecurity influences mental health and how poor mental health may contribute to physiological processes of the stress response system that can impair socio-economic productivity. Jessica holds an MA in the Anthropology of Development from the University of Sussex (2007). Prior to pursuing a doctorate degree, she worked for three years in the non-profit world in advocacy for equitable health care access. Presentation: Worried Sick: Investigating Linkages Among Food Insecurity, Mental Health and Productivity in the Ghanaian Savanna Abstract: My dissertation research investigates the effectiveness of coping with food insecurity in a subsistence society in northern Ghana that is transitioning to a peri-urban environment. Research shows that food insecurity predicts poor mental health (Cole and Tembo 2011; Hadley and Patil 2008; Lund et al. 2010; Nanama and Frongillo 2012). My project is equally concerned with the reverse prediction, whether poor mental health leads to reduced capacity to assure access to food. Where food accessibility depends upon managing diverse and labor-intensive economic activities meant to procure social and material needs, poor mental health may perpetuate conditions of vulnerability. I propose that this pathway is mediated by physiological stress responses as measured through blood pressure and the stress hormone cortisol. In turn, I propose that poor mental health, supplemented by elevated cortisol profiles and blood pressure may result in deleterious behavioral responses seen in household socio-economic decision-making processes. I therefore investigate how poor mental health may influence long-term adaptations. I implemented the WEAI in my fieldwork in Ghana to investigate whether empowerment scores have any relationship (correlative or predictive) with food security scores.
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IFPRI Gender Methods Seminar, May 28, 2015: Exploring Food Security and Mental Health in Upper West Ghana Through Empowerment
- 1. Exploring Food Security and Mental Health in Upper West Ghana Through Empowerment JESSICA HAM UNIVERSITY OF GEORGIA
- 3. UPPER WEST GHANA WHY FOOD INSECURITY, WHY HERE? 33% of the population in the north is food insecure 6% of the population in the south is food insecure 42% of the Wa West district is food insecure 2009; 2012 WFP Setting the scene
- 5. Food Insecurity and Mental Health Survey Results
- 6. Calculated WEAIIndexes Women Men Disempowered Headcount (H) 67.24% 3.39% Empowered Headcount (1-H) 32.76% 96.61% Average Inadequacy Score (A) 44.02% 51.677% Average Adequacy Score (1-A) 55.98% 48.33% Disempowerment Index (M0 = HXA) 0.296 0.018 5DE Index (1-M0) 0.704 0.982 No. of observations used 58 59 Total observations 58 59 % of Data used 100.00% 100.00% % of women without gender parity (HGPI) 29.91% % of women with gender parity (1-HGPI) 70.09% Average Empowerment Gap (IGPI) 29.64% GPI (1 - HGPI x IGPI) 0.911 No. of observations used 45 Total no. of dual households 45 % of Data Used 100.00% WEAI (0.9X5DE+.1XGPI) 0.725 0.716 27.9% (f) 76.2% (m) 26.9%
- 7. WEAI by Community CHANSA Indexes Women Men Disempowered Headcount (H) 77.78% 3.23% Empowered Headcount (1-H) 22.22% 96.77% Average Inadequacy Score (A) 40.00% 43.33% Average Adequacy Score (1-A) 60.00% 56.67% Disempowerment Index (M0 = HXA) 0.311 0.014 5DE Index (1-M0) 0.689 0.986 No. of observations used 27 31 Total observations 27 31 % of Data used 100.00% 100.00 % % of women without gender parity (HGPI) 32.76% % of women with gender parity (1- HGPI) 67.24% Average Empowerment Gap (IGPI) 26.54% GPI (1 - HGPI x IGPI) 91.31% No. of observations used 25 Total no. of dual households 25 % of Data Used 100.00% WEAI (0.9X5DE+.1XGPI) 0.711 TAMPIANI Indexes Women Men Disempowered Headcount (H) 58.06% 3.57% Empowered Headcount (1-H) 41.94% 96.43% Average Inadequacy Score (A) 48.70% 60.00% Average Adequacy Score (1-A) 51.30% 40.00% Disempowerment Index (M0 = HXA) 0.288 0.021 5DE Index (1-M0) 0.712 0.979 No. of observations used 31 28 Total observations 31 28 % of Data used 1 1 % of women without gender parity (HGPI) 27.12% % of women with gender parity (1- HGPI) 72.88% Average Empowerment Gap (IGPI) 33.33% GPI (1 - HGPI x IGPI) 90.96% No. of observations used 20 Total no. of dual households 20 % of Data Used 100% WEAI (0.9X5DE+.1XGPI) 0.736 Measure Number of Subjects Z Statistic P-Value Adequacy Score 117 0.19 0.8517
- 8. Relating Food Insecurity and Mental Health N=406 Rho=.623 P<.0001 b=.78 P<.0001 R2=.38
- 9. Gendered Analysis Measure Number of Subjects Z Statistic P-Value Food Security 198 men 208 women -3.41 P<0.0007 Mental Health 198 men 208 women -3.12 P<.0018 Male(0) Female(1) b p R2 N=198 .67 P<.0001 .33 N=208 .82 P<.0001 .39
- 10. Relationship Between Adequacy and Food Security/Mental Health Measure Number of Subjects Rho P-Value Food Security Time 1 99 -0.1771 0.0795 Food Security Time 2 111 -0.1121 0.2417 Food Security Time 3 113 -0.0754 0.4272 Mental Health Time 1 100 -0.1866 0.0631 Mental Health Time 2 111 0.0108 0.9101 Mental Health Time 3 113 -0.0222 0.8156
- 11. Next Steps Look at how individual domains/indicators relate to food insecurity Look for a relationship between adequacy scores and individual domains and BMI Look to see if adequacy scores associate with agricultural yield
- 12. Upper West Livelihoods Shea fruit Charcoal Farming Ongoing narrative of continuity and change Construction
- 13. Ethos of Unity
- 14. Acknowledgements Research support: WEAI Dissertation Fellowship Borlaug Food Security Research Grant Statistical assistance: University of Georgia Statistical Consultancy Center (Dr. Kim Love-Myers and Fei Lu)
Editor's Notes
- Introduction to project variables and relationships sought WHO warns that common mental disorders will be the most prevalent health burden by 2020 Increasing attention to how food insecurity, as a condition of concern for many populations across the world, relates to mental health outcomes. But little work that investigates, so what? I’m tracing a feedback loop between food insecurity, poor mental and physical health outcomes and socio-economic productivity (aka livelihood activities) However, I suspect that I’m not going to prove a significant relationship between all of these variables as I think that there are strong social mechanisms in place to ensure that poor mental health symptoms do not manifest into serious conditions. As such, what can food insecurity be attributed to? Loosely I’ve been thinking in terms of a framework of vulnerability—but the WEAI is a formal tool and a standardized way to look at differences in social and economic access/opportunities that structure access to food within a theoretical framework of vulnerability.
- So why is food insecurity an important condition to look at in the Upper West? As we already know, its part of the FtF zone of influence. In 2009 the WFP conducted an assessment that establishes that 33% of the population in the 3 northern regions of Ghana are food insecure—compared to 6% of the population in the southern 2/3 of the country. In 2012 they did an additional assessment to look at how food insecurity is variable across these 3 northern regions. I work in a district that straddles the Wa West district—the district with the highest rates of food insecurity at 42%.
- So why mental health? Is mental health even a problem here? By mental health I’m interested in symptoms of worry and anxiety. In preliminary research in the summers of 2011 and 2012 I learned about a local stress bound illness called worry sickness and created a symptom checklist based on the symptoms of worry sickness—this closely resembles the Hopkins Symptom Checklist. Additionally, I conducted a free listing and ranking exercise so as to map people’s worries. I asked people to exhaustively list the things that caused them to worry. As this graph shows, food was the most frequently reported thing that causes worry. However, school fees are cited almost as frequently, but as a more pressing concern. This—in addition to other data I have on seasonal dietary diversity and dietary preference—speaks to what, exactly, food insecurity is in this context.
- 3 seasonal iterations of surveying in two neighboring communities establish food insecurity and mental health standing (n=140 individuals). The food insecurity survey is composed of 8 questions inquiring about the individual perception of the household experience with food quantity and quality within in the past month. The mental health survey inquires about the presence and rate of occurrence of 14 contextually relevant symptoms of anxiety and depression. A mean score is derived from the 3 survey iteration scores for both variables. This mean score is treated as a continuous variable in correlation analysis as well as a simple linear regression.
- The WEAI was implemented with 117 individuals from the sample and was modified to fit the context. The most noteworthy modification that I made was to eliminate module G5 as in trial runs of the survey, this section caused a lot of confusion and elicited complaints of repetitiveness. My research assistants and I conducted the WEAI at the end of my fieldwork—and I found it to be an extremely strong advantage to conduct this survey with a group of people I was already quite familiar with. We knew what kind of farming they were doing. We knew what livelihood activities they participated in. If a woman we knew to be a charcoal trader said she didn’t participate in trading, we could question her. However, what became challenging was when that same woman would say that she had little control over her income and we suspected that she had a lot of control over her income. This is a challenge of the traditional model clashing with the model of reality. This is a patriarchical society—the default answer is to say that your husband has control—even if that is not the case. The traditional model is what still resonates in peoples minds even if what is happening in reality does not follow that model. Index results for this context in Ghana show similar results to the much larger surveying project throughout the 3 northern regions. My calculated index is 0.725 compared to 0.716.
- Because adequacy scores are indicative at the individual level, adequacy scores are what I’ve focused on thus far in my analysis of the results from the empowerment index. We did a Wilcoxon rank sum to see if there was any significant difference in adequacy scores between the two communities that compose the sample. This test shows that there is no significant difference in adequacy scores
- Gender roles are changing and at the same time not changing. Opportunities are changing, but expectations for what you should do as a husband/wife are really not. Men remain largely culturally constrained to farming. It is still their role to farm for their family. Holding onto land and ensuring it remains productive is increasingly important in this context of fairly rapid urbanization. These communities hold dear the ability to produce as much food as possible for ones self so as to bypass the high and increasingly spastic price of food at market. However, farming is hard and expensive. Rainfall patterns are changing. Soil fertility is decreasing. These households are increasingly diversifying their livelihood portfolios. These is easier for women to do since they don’t bear the ultimate responsibility for farming. Yes they have to help their husbands on the farm, but they do not have to devote all of their time to farm work. They are the ones allowed to trade in shea nuts. They are enabled to produce and trade in charcoal. These are opportunities that are taboo for men to engage in—though they are slyly engaging in them with their wives. The opportunities that men have for diversifying away from farming are activities that do not put them in charge of their own labor, their own time. There is a lot of wage labor in a nearby urban center, but this is work that you have to devote your entire day to. One man who was trying to manage day labor construction work and his farm work found this to be incredibly stressful—when he was building blocks for a wage he was worried about his farm. When he was able to work on his farm he was worried that he wasn’t able to earn money for fertilizer that his farm really needed. It’s a catch-22. Women on the other hand have always had economic portfolios that require this ongoing balancing of time and energy to farm work, domestic work, and other income earning activities like beer brewing and shea nut trading. And that’s not to say that they are not overloaded with work. Nothing could be further from the truth.
- Unity is what builds health in an individual and within a marriage and within a family. Unity is being able to sit down and express your worries and concerns and to discuss them and to cooperatively come up with a solution. Unity also leads to empowerment.