Integrating Resource Access 19May2015

Integrating Resource Access, Livelihoods and Human Health around Lake Victoria, Kenya

Kathryn Joan Fiorella

A dissertation submitted in partial satisfaction of the

Requirements for the degree of

Doctor of Philosophy

Environmental Science, Policy & Management

in the

Graduate Division

of the

University of California, Berkeley

Committee in charge:

Professor Justin S. Brashares, Chair Professor Lia H. Fernald Professor Claire Kremen

Summer 2015

! ! ! ! ! ! ! ! ! ! ! ! Integrating Resource Access, Livelihoods and Human Health around Lake Victoria, Kenya

! Abstract

Integrating Resource Access, Livelihoods and Human Health around Lake Victoria, Kenya

Kathryn Joan Fiorella

Doctor of Philosophy in Environmental Science, Policy & Management

University of California, Berkeley

Professor Justin S. Brashares, Chair

While ecosystem and human health have been closely linked, the mechanisms through which natural and social systems interact to support human health are rarely understood. Yet the rapid transformation of Earth’s natural systems makes appreciating the drivers and ramifications of environmental change for human health particularly critical. To illuminate these links, I analyze the effects of changing resource access on household livelihoods, food security, health and nutrition. Specifically, I use the case of Lake Victoria, Kenya, to examine ways individuals and households respond to and affect fish availability. I employ both qualitative and quantitative methodologies, including a longitudinal household survey, ecological monitoring of fish catch, and qualitative in-depth interviews. My analyses examine a bi-directional relationship between fish availability and the health of people who depend on fish resources. First, I analyze how participation in fishing livelihoods affects fish consumption and food security. Next, I examine the bounds of resource availability in time and space in affecting household fish consumption. Further, I assess the impact of illness in fishers on fishing methods, and thereby fishery sustainability. Finally, I analyze how fish declines affect women’s access to fish, and, in particular, the power dynamics of transactional fish-for-sex relationships and HIV risk. Through these analyses, I aim to illuminate both the extensive effects of environmental change and mechanisms that tie the health of people and their environment. ! !

! ! ! 1 Dedication

I dedicate my dissertation to my parents, Joan and John Fiorella. I am deeply grateful to my parents for their unwavering support, especially in getting me back on my feet and as I traveled back to East Africa.

! i Table of Contents

Acknowledgements

Chapter 1. Introduction

Chapter 2. Fishing for Food? Analyzing Links Between Fishing Livelihoods and Food Security

Chapter 3. Fish Availability and Household Fish Consumption

Chapter 4. Effects of Human Illness on Environmental Sustainability

Chapter 5. Transactional Fish-for-Sex Relationships Amid Declining Fish Access in Kenya

Chapter 6. Concluding Remarks ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

! ii Acknowledgements

I have been fortunate to receive the wisdom and guidance of two exceptional advisors: Justin Brashares and Lia Fernald. Justin, I am grateful for your dedication to mentorship, unwavering support, and enthusiasm for my interdisciplinary pursuits. My graduate school experience has been rich in exceptional opportunities to develop and lead projects and collaborations. Thank you for making these experiences possible and guiding me through them. Lia, I am grateful to you for welcoming me into your lab group, advising my studies in epidemiology and nutrition, and keeping me grounded in the study details. Thank you for championing and supporting my efforts to venture into new academic arenas.

I am grateful, also, to my wonderful dissertation and orals committee members for their thoughtful input: Claire Kremen, Louise Fortmann, and Isha Ray. In addition, Matthew Potts, Craig Cohen, Carol Camlin and Elizabeth Bukusi have offered tremendous guidance for this work.

To my current and former labmates in the Brashares and Fernald Labs, thank you for your friendship, advice and encouragement. Interacting with you all has been an honor and a pleasure.

To my roommates in Berkeley, Hekia Bodwitch, Charlotte Jennings, Ashley Clark, and Emily Apte, I am incredibly grateful for your perspective, emotional support, and travel companionship since the beginning of our graduate school journey.

To Darrel, Hans, Stef and the staff at Trapeze Arts, thank you for keeping me grounded by teaching me to fly.

My research would not have been possible without the generous participation of the Mfangano community, the enthusiasm of Organic Health Response, and the hard work and dedication of a remarkable team in Kenya. Dan Omollo, your excellent leadership and focus on community communication and capacity building have been instrumental in the success of our efforts in Kenya. Brian Mattah, your work ethic, attention to detail, and willingness to learn new programs are remarkable. To Janet, Mary Janet, Vallary, Abdi, Jacky, Maureen, Beatrice, Wilson, Julius, and Kevin, thank you for your tireless efforts in the community.

To Matt Hickey, Chas Salmen, Erin Milner and Erika Gavenus thank you for your salient feedback, trouble-shooting expertise, and being the best collaborators I could ask for. Andy Lyons, your patience for database inquiries and support went far beyond the call of duty.

I am deeply grateful to Pam, Mohamed, Lydia, Nancyla, Bon, Awiko, Amam, Chris, Ouma, Brian, Dawn, Toto, and Lucky, for making me a part of their family in Kenya and ensuring that my time in Kenya is rich in experiences that extend beyond research activities.

Many thanks to Rachel Mwakisha, Petronilla Njenga, and Raphael Ondondo in Kenya and Leaf Grenoble, Alexis Clasca, Judy Smithson, and Roxanne Heglar for their exceptional patience in providing financial, CPHS, permitting, and administrative support.

! iii I have been fortunate to receive instrumental financial support from the National Science Foundation Graduate Research Fellowship Program, Doctoral Dissertation Research Improvement Grant, and Coupled Natural and Human Systems Grant (NSF-GEO CNH115057); Philomathia Foundation; USAID Partnerships for Enhanced Engagement in Research; Andrew and Mary Thompson Rocca Fellowship; One Health Summer Research Fellowship; Foreign Language and Area Studies; Environmental Science, Policy & Management Summer Grant, Sigma-Xi Grants-in-Aid of Research, and Sara’s Wish Foundation.

Finally, I would not be where I am without my wonderfully supportive family. To my parents and Betsy, I am grateful now and always for your love, concern, encouragement. And last but certainly not least, thank you Dan, for becoming my best friend and sharing this journey with me – in triumphs, challenges, and countless flights across the US and beyond.

! iv Chapter(1.(Introduction( ( While ecosystem and human health have been closely linked (Corvalán et al. 2005; Carpenter et al. 2009), the mechanisms through which natural and social systems interact to support health are rarely understood. Researchers have long recognized that ecosystem transformation and resource access cannot be understood without consideration of the political and economic structures within which they are embedded (Robbins 2004; Ribot and Peluso 2003; Neumann 2005). Recently, the coupling of people and the environment has been theorized through a lens of coupled human and natural systems or socio-ecological systems (Liu et al. 2007b; Walker et al. 2004; Ostrom 2007). In calling for a broader interdisciplinary integration of research on social and natural systems, these efforts aim to develop new insights into the complexity and dynamism of such systems (Liu et al. 2007a; Schlueter et al. 2012; Ostrom 2009). In particular, these approaches emphasize, sustainability, resiliency and the linked fates of human and natural systems (Adger 2000; Folke 2006).

Nowhere are the fates of people more closely tied to that of the environment than for individuals and households reliant on natural resource access for food and livelihoods. For the 47% of the global population living in rural areas of economically developing countries, natural resources often provide basic needs (World Bank 2013). These rural households are on the frontlines of global environmental change and resource stewardship, while coping with the highest burdens of malnutrition and poverty. For instance, fish contribute over 25% of dietary protein in many poor countries and can contribute 90% in some island states, coastal regions and inland areas near lakes (FAO 2005). At the same time, fishery sustainability is at risk in many of the world’s fisheries, particularly in the tropics (Worm et al. 2006; Pauly et al. 1998). While ecologists agree that unsustainable harvest can have catastrophic consequences for ecosystems and the services and livelihoods they provide, we need to better understand the economic, social and health factors that shape harvested systems to determine access to beneficial resources, and, ultimately, these systems sustainability.

Inquiries that tie ecosystem function and human well-being are predominantly at global and regional scales (Corvalán et al. 2005). While much research has sought to understand household reliance on natural resources (Adams et al. 2004; Corvalán et al. 2005), we must integrate the dynamics of ecosystems that provision resources and feed back to affect household well-being to truly understand these systems. An understanding of what effects daily decisions of rural households concerning the use of natural resources is necessary to both human health and ecological sustainability (Dasgupta 2008; Persha et al. 2011).

I explore the inter-relationships between the dynamics of resources and human reliance on those resources by focusing my analysis on the role of fish access in the inland Lake Victoria fisheries. I examine how availability of and access to fishery resources shapes’ households decisions about livelihoods and fish consumption in Western Kenya, and how household well-being influences use of and access to fishery resources. My dissertation links both fish availability and, simultaneously, fishing effort and livelihoods, fishery access, fish consumption, and nutritional status among people who rely on fishery resources. I ask first how environmental change constrains food resource access to affect food, livelihood, and nutrition security. I ask next how social conflict and poor health feed back to affect livelihoods and environmental sustainability.

! 1 The chapters of this dissertation each examine a particular facet of the interconnected dimensions of social and ecological systems around resource availability, livelihoods, food access, and health and nutrition.

Interdisciplinary Contributions

In addressing the connection between human and ecological health, I employ interdisciplinary methodologies and approaches that draw from ecology, public health and political ecology. The literature on sustainable livelihoods integrates the multiple avenues through which livelihoods link natural resource access to human well-being (Chambers and Conway 1992; Chambers 1995; de Sherbinin et al. 2008; Ellis 2000). In theorizing multiple aspects to capital, including social, natural, physical, human and financial, this approach underscores that ways that households navigate their advantages and deploy coping strategies (Allison and Ellis 2001). Moreover, Ribot and Peluso’s (2003) theory of access frames the distinction between rights to benefit from resources and the ability to do so. Resource availability or decline may have differential effects on different people, depending on realized resource access, income and livelihood choices (Ribot and Peluso 2003; Allison 2004). This theory of access ties a livelihood approach to the resources engaged in livelihoods. In this dissertation I examine access separately from resource availability. Access, and the ways it shapes and is shaped by human health is a central concern of this work.

Further, the questions in this dissertation link to the ecological literature on ecosystem services. Work on ecosystem services asserts that the environment provides enormous, quantifiable benefits for human populations through, among other things, nutrient cycling, clean air and water, and food production and provisioning (Worm et al. 2006; Costanza et al. 1997). The integration of health into ecosystem services extends this literature to appreciate the effects of changing ecosystems on the spread of infectious disease and, increasingly, the supply of nutritious food (Myers et al. 2013; Golden et al. 2011). Integrally intertwined into the services that ecosystems provide is the idea of natural resources comprising an income and nutritional safety net in times of hardship (Milner-Gulland et al. 2003; de Merode et al. 2004).

Finally, public health underscores topics in food and nutrition security, extending the links between natural resources and livelihoods to explicitly assess human well-being. An extensive literature provides an assessment of the scope of food insecurity and malnutrition as well as strategies for measuring, understanding, and addressing this challenge (Black et al. 2013; Bhutta et al. 2013). Some 805 million people are chronically undernourished (FAO et al. 2014), and concerns over a population quickly growing to 9 billion have closely tied food security to the environment (Godfray et al. 2010). The broad recognition that nutritional gains are dependent on including, also, approaches in other sectors that are sensitive to nutrition (Ruel et al. 2013) underscores growing recognition of the importance of linking nutrition, food access, and the environment. Moreover, the integration of food security with other health outcomes, particularly ties between food insecurity and HIV vulnerability (Weiser et al. 2007; Weiser et al. 2014), further links health to livelihoods and the environment (Allison and Seeley 2004b; de Waal and Whiteside 2003; Talman et al. 2012; Fiorella 2013).

! 2 The Case of Lake Victoria

The previous half-century of ecological and social change that characterizes Lake Victoria is emblematic of the environmental change and harvest pressure felt in communities across the world. The introduction of non-native, predatory Nile perch by the British colonial authorities in the 1960s influences every facet of the Lake Victoria fisheries today. Designed to create a productive fishery with a more commercially viable species, the introduction precipitated a boom in Nile perch that transformed and commercialized Lake Victoria (Awange and Ong'ang'a 2006). Predation by Nile perch caused the largest extinction event of modern time and the demises of over 300 cichlid species (Witte et al. 1992). At the same time, Nile perch motivated explosive growth of fishing through the 1980-1990s, drove migration to Lake Victoria, and revamped the socio-ecologic dynamics of the lake (Owino 1999; Medard 2012; Matsuishi et al. 2006; Hecky et al. 2010). Recent data suggest a marked decline in fish catch despite sustained fishing effort (Njiru et al. 2007; Matsuishi et al. 2006). Declining fish catch threatens to limit fish availability and reverberate from the depth of the lake to the people living on the lakeshores who are dependent on fishing for both food and income.

Dissertation Methodologies and Overview

To understand how changes in fish catch affect household behaviors I pair ecological monitoring of fish catch with a longitudinal household survey. In collaboration with the Kenyan State Department of Fisheries, which, alongside Mfangano Island’s 19 Beach Management Units, co- manage the fish landing sites, I monitored daily fish catch, prices, and fishing effort. Fish catch is monitored for the two key commercial species, Nile perch (L. niloticus) and Dagaa (locally called ‘omena’ in Kenya, R. argentea). Simultaneously, I conducted a longitudinal cohort study of 303 randomly sampled local households to understand the associations between changes in fish catch and household behaviors. The research study ran from August 2012-March 2015 with regular follow-up time points (every 3 months) for household data collection and daily fish catch data collection.

To assess household responses to fish availability, I examined household consumption of fish and food security to evaluate links between fish access and fish consumption. Using a cross- sectional household survey (n=111), I find that participating in fishing as a livelihood was not associated with household fish consumption or food security. I next extend this analysis with a cohort study (n=311, 4 time points) to describe patterns of fish consumption, purchase, and child nutritional status. In addition, this work examines the role of fish availability in affecting fish consumption and the bounds in time and space by which fish availability mediates household consumption.

Further, I assess the links between morbidity, or the experience of illness, and environmental impact. In a cohort of male fishers (n=256, 4 time points), I examine the ways morbidity affects fishing behaviors and the contributions of illness to reducing, increasing, or changing fishing effort. Although fishers do not appear to curb fishing effort when ill, they moderate physical effort in the selection of fishing methods that are more likely to be near or inshore, have low physical demands, and be illegal and environmentally destructive.

! 3 Finally, I examine how changes in fish availability affect women’s access to fish and, in particular, transactional fish-for-sex relationships used to secure fish access. Fish declines affect the initiation, duration, and power dynamics of fish-for-sex relationships. In particular, fish availability affects women’s negotiations in the economic (e.g. fish price, quantity) and sexual (e.g. condom use) aspects of their relationships.

In this work, I strive to provide case studies that exemplify a range of ways – food access, morbidity, livelihood dependence, sexual relationships, and risk – that human health is linked to ecosystem function and resource access. In providing case studies, I examine particular mechanisms and dynamics to provide examples that, I hope, help us better understand the interwoven dynamics, synergies, and oppositions in our social and natural systems.

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! 5 Ostrom, E. (2007). A diagnostic approach for going beyond panaceas. Proceedings of the National Academy of Sciences of the United States of America, 104(39), 15181-15187. Ostrom, E. (2009). A General Framework for Analyzing Sustainability of Social-Ecological Systems. Science, 325(5939), 419-422. Owino, J. (1999). Traditional and Central Management Systems of the Lake Victoria Fisheries in Kenya. Socio-economics of the Lake Victoria Fisheries Project Report No.5. Nairobi: IUCN. Pauly, D., Christensen, V., Dalsgaard, J., Froese, R., & Torres, F. (1998). Fishing Down Marine Food Webs. Science, 279(5352), 860-863. Persha, L., Agrawal, A., & Chhatre, A. (2011). Social and Ecological Synergy: Local Rulemaking, Forest Livelihoods, and Biodiversity Conservation. Science, 331(6024), 1606-1608. Ribot, J. C., & Peluso, N. L. (2003). A Theory of Access. Rural Sociology, 68(2), 153-181. Robbins, P. (2004). Political ecology: a critical introduction: Wiley-Blackwell. Ruel, M. T., Alderman, H., & Maternal Child Nutr Study, G. (2013). Nutrition-sensitive interventions and programmes: how can they help to accelerate progress in improving maternal and child nutrition? Lancet, 382(9891), 536-551. Schlueter, M., McAllister, R. R. J., Arlinghaus, R., Bunnefeld, N., Eisenack, K., Hoelker, F., et al. (2012). NEW HORIZONS FOR MANAGING THE ENVIRONMENT: A REVIEW OF COUPLED SOCIAL-ECOLOGICAL SYSTEMS MODELING. Natural Resource Modeling, 25(1), 219-272. Talman, A., Bolton, S., & Walson, J. L. (2012). Interactions Between HIV/AIDS and the Environment: Toward a Syndemic Framework. American Journal of Public Health, 103(2), 253-261. Walker, B., Hollin, C. S., Carpenter, S. R., & Kinzig, A. (2004). Resilience, adaptability and transformability in social-ecological systems. Ecology and Society, 9(2). Weiser, S. D., Leiter, K., Bangsberg, D. R., Butler, L. M., {Percy-de Korte}, F., Hlanze, Z., et al. (2007). Food insufficiency is associated with high-risk sexual behavior among women in Botswana and Swaziland. PLoS medicine, 4, 1589-1597; discussion 1598. Weiser, S. D., Palar, K., Frongillo, E. A., Tsai, A. C., Kumbakumba, E., Depee, S., et al. (2014). Longitudinal assessment of associations between food insecurity, antiretroviral adherence and HIV treatment outcomes in rural Uganda. AIDS, 28(1), 115-120. Witte, F., Goldschmidt, T., Wanink, J., Vanoijen, M., Goudswaard, K., Wittemaas, E., et al. (1992). The Destruction of an Endemic Species Flock - Quantitative Data on the Decline of the Haplochromine Cichlids of Lake Victoria. Environmental Biology of Fishes, 34(1), 1-28. World Bank (2013). Agriculture and Rural Development. In T. W. B. Group (Ed.). Washington, DC. Worm, B., Barbier, E. B., Beaumont, N., Duffy, J. E., Folke, C., Halpern, B. S., et al. (2006). Impacts of biodiversity loss on ocean ecosystem services. Science, 314(5800), 787-790.

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! 6 Chapter 2. Fishing for Food? Analyzing Links Between Fishing Livelihoods and Food Security

This chapter has been previously published and is reproduced here with kind permission of the co-authors and Springer.

Fiorella, K.J., Hickey, M.D., Salmen, C.R., Nagata, J.M., Mattah, B., Magerenge, R., Cohen, C.R., Bukusi, E.A., Brashares, J.S., Fernald, L.H. 2014. Fishing for Food? Analyzing links between fishing livelihoods and food security around Lake Victoria, Kenya. Food Security. 6(6): 851-860.

ABSTRACT

Food-producing livelihoods have the potential to improve food security and nutrition through direct consumption or indirectly through income. To better understand these pathways, we examined if fishing households ate more fish and had higher food security than non-fishing households around Lake Victoria, Kenya. In 2010, we randomly sampled 111 households containing 583 individuals for a cross-sectional household survey in a rural fishing community. We modeled the associations between fish consumption and food security and fishing household status, as well as socioeconomic variables (asset index, monthly income, household size) for all households and also for a subset of households with adult male household members (76 % of households). Participating in fishing as a livelihood was not associated with household fish consumption or food security. Higher household fish consumption was associated with higher household income and food security, and was weakly associated with lower household morbidity. Household food security was associated with higher incomes and asset index scores. Our results suggest socioeconomic factors may be more important than participation in food- producing livelihoods for predicting household consumption of high quality foods.

1. INTRODUCTION

Gains in food production are often assumed to improve household food security and nutrition among people engaged in food-producing livelihoods. However, somewhat paradoxically, the majority of the world’s 50 million small-scale fishers and 2.6 billion farmers are food insecure (FAO 2012a). Understanding why those engaged in food production so often are food insecure is complicated by the intricate pathways from fishing nets to dinner plates, and the dynamics of production systems affected by such factors as resource depletion, globalized markets, price fluctuations and climate change.

Fishing livelihoods are of particular concern as 90% of fishers work in small-scale fishing operations and most operate in economically developing countries (FAO 2012b). Fish serves as the primary protein source for 1 billion people worldwide and often contributes the large majority of dietary protein in areas near fisheries, such as the shores of Lake Victoria (FAO 2012b). Fish may serve as both a nutritional safety net and a significant source of calories,

! 7 protein, and micronutrients (Milner-Gulland et al. 2003; Kawarazuka and Bene 2010). The importance of fishery resources to meet minimum dietary requirements is further exemplified by the fact that fluctuations between availability of fish has driven trade-offs in the consumption of other wildlife resources (Brashares et al. 2004). Complicating access to fish, fisheries worldwide, including Lake Victoria’s fishery, are often globalized, gendered, and threatened (Pauly et al. 2005; Geheb et al. 2008; Njiru et al. 2007).

The importance of fishery systems to meet basic needs coupled with the range of threats they face has given rise to livelihood interventions, which often promote fishery management, aquaculture, and agricultural alternatives (Allison 2011; FAO 2010). However, evaluations that measure the effectiveness of fishery interventions, like those of agricultural interventions, have typically shown limited nutritional impact (Girard et al. 2012; Kumar and Quisumbing 2010). Limited benefits for macro- and micro-nutrient intake suggests that participation in food-based livelihoods may not always link directly to increased food consumption.

Further, adverse health events can potentially affect a household’s ability to take part in livelihood activities and access fish or other resources. Illness may reduce fishing participation and income, with direct and downstream effects on nutritional status, food production, household income, spending patterns, and, ultimately, food security. High morbidity within a household may also affect natural resource stewardship and inter-generational knowledge transfer about resource use (Salmen 2009; Talman et al. 2012; Fiorella 2013). HIV/AIDS associated morbidity is of unique concern to fishing communities in sub-Saharan Africa (Allison and Seeley 2004a), and a formidable challenge in our focal communities on Mfangano Island, Kenya, where HIV prevalence is estimated at over 25% (Kenya Ministry of Health 2013).

While households that rely on fishing for their livelihoods are assumed to consume more fish than other households, this assumption has rarely been tested (Kawarazuka and Bene 2010). In fact, we know of no study that compares fish consumption between fishing and non-fishing households within a fishing community. To begin to understand associations among livelihoods, food consumption and food security, we compared the socioeconomic status and diets of fishing households and non-fishing households on Mfangano Island on Lake Victoria, Kenya. Specifically, we used a cross-sectional household survey to ask whether fishing households consumed more fish or had higher food security, and to quantify how income and morbidity mediated these relationships.

2. MATERIALS AND METHODS

Study Site

Our research focuses on Mfangano, an island of 65km2 in Lake Victoria, located within Homa Bay County in Nyanza Province, Kenya. The 1960’s introduction of non-native Nile perch into Lake Victoria precipitated a crash in the lake’s biodiversity and caused the broad decline of cichlid species (Witte et al. 1992). While the growth of an export industry for Nile perch spurred economic development, the people of Nyanza province continued to experience the highest poverty rates in Kenya (Kenya National Bureau of Statistics and ICF Macro 2010). The Nile

! 8 perch fishery expanded quickly through the 1990s, but recent data suggest a decline in fish catches in Kenya, despite sustained fishing effort (LVFO 2012). Within lakeside communities, households today remain reliant on artisanal fishing and are vulnerable to fish declines. On Mfangano, involvement in the fishery, both for trade of fish and subsistence use, is widespread. Mfangano has limited health infrastructure and electricity, and no running water or paved roads. Food insecurity is common throughout Mfangano and ubiquitous among people living with HIV/AIDS (Nagata et al. 2012; Nagata et al. 2013).

Survey Methods

In August–October 2010, we conducted a cross-sectional survey in three villages on Mfangano Island. Mfangano has a network of government trained Community Health Workers and each is assigned to provide health outreach to a group of households. Household assignment to community health workers is exhaustive and mutually exclusive, providing for representative sampling within these communities. We stratified our sampling by community health worker and randomly sampled 111 households with 583 individuals, or approximately one third of all households.

We approached female and male heads of household to provide consent for study participation. All of the households we approached consented to participate in the study. A trained enumerator visited participating households to complete a one-hour questionnaire covering the following domains: 1) household and demographic features; 2) measures of food, water, and income security; 3) household morbidity via reports of illness frequency. Female heads of household responded to all questions in these domains.

We developed the survey through a compilation of validated behavioral and social science instruments and made modifications for the local context (Appendix I). We translated the survey into Dholuo and back-translated into English to ensure consistency of meaning. We administered the survey in Dholuo. The Committee on Human Research at the University of California, San Francisco and the Ethical Review Committee at the Kenya Medical Research Institute approved this research. We obtained written consent from study participants prior to enrollment.

Characterization of Variables

We characterized a household as engaged in fishing as a livelihood activity if the household mother reported the occupation of any household member as fisher or reported Nile perch fishing as a primary income earning activity (Appendix I). Adult males dominate Nile perch fishing, and a relatively large percentage (22%) of households did not contain an adult male, thus, we conducted separate analyses for the subset of households with an adult male and all the households combined.

We characterized household socioeconomic status based on reported monthly income, an asset scale, highest level of maternal education and household size. Monthly income was log- transformed to approximate a normal distribution. Three outlying monthly income data points, determined by the interquartile outlier rule and representing a near doubling of the next closest incomes, were omitted. Models created with these outliers included show similar patterns of

! 9 significance and contribution of other variables, but with inflated odds ratios for monthly income. We conducted a principle component analysis (PCA) of an 11-item asset scale to develop a single asset measure among several potentially collinear predictors. Our results determined that all 11 predictors were necessary in explaining variance so all items were included in the scale (Vyas and Kumaranayake 2006). We assessed food security with a subset of the Household Food Insecurity Access Scale (HFIAS; (Coates et al. 2007). HFIAS scoring methods were used to categorize households as food secure/mildly food insecure or moderately/severely food insecure (Coates et al. 2007).

We measured levels of fish consumption by reported frequency of household consumption of fish. For multivariate logistic regression, we coded fish consumption as a binary variable such that households consuming fish never or rarely were scored as zero and households consuming fish sometimes, often or frequently were scored as one.

We assessed morbidity based on reporting from the household mother on whether any adult household member was too sick to go to work or school on any day in the month preceding the survey. We calculated both adult morbidity and adult male morbidity as binary household variables.

Statistical Analyses

We conducted statistical analyses using Stata Version 12.1 (StataCorp LP; Texas, USA). We compared demographic characteristics between fishing and non-fishing households using Welch unequal T-tests. We performed bivariate and multivariate logistic regressions to assess the variance explained by each independent variable (monthly income, asset scale, household size, fishing household, household morbidity, and fish consumption/food security) on each outcome variable (fish consumption, food security). We selected multivariate models through the evaluation of variables proposed and retention of those variables that improved model performance. We confirmed model selection with likelihood ratio tests. We checked all variables for multicollinearity and confirmed a variance inflation factor <2.

We modeled logistic regressions separately for all households in the sample, and for households containing an adult male. We calculated 95% confidence intervals (CIs) for all odds ratios and report the p-value for the associated regression coefficient.

3. RESULTS

Descriptive statistics of the 111 households sampled are found in Table I. Fishing households did not report increased fish consumption or food security in comparison to non-fishing households (Table II). This remained true when our analysis included only households with an adult male present (Table III).

In multivariate analyses, high household fish consumption was associated with monthly income (Odds Ratio [OR] 2.40, 95% Confidence Interval [CI] 1.45 – 3.98) and food security (OR 1.18, 95% CI 1.00-1.39) compared to households with low fish consumption. Adult morbidity (OR

! 10 0.48, 95% CI 0.19 – 1.16) was retained in our model predicting fish consumption, but was not statistically significant. Household food security (food secure / mildly food insecure) was associated with the asset index (OR 1.37, 95% CI 1.04 – 1.82) and monthly income (OR 1.67, 95% CI 1.02 – 2.74) compared to households who were moderately or severely food insecure.

In households with an adult male member, high fish consumption was positively associated with monthly income (OR 2.67, 95% CI 1.48 – 4.82) compared to households with low fish consumption. In households with an adult male member, food security was positively associated with an increased asset index score (OR 1.48, 95% CI 1.07 – 2.04) and monthly income (OR 2.16, 95% CI 1.12 – 4.18) comparedAuthor's to food personalinsecure households. copy K.J. Fiorella et al.

Table 1 Comparison of household characteristics for each of the mea- Welch two-sample t-tests for unequal variances; only adult morbidity was sured variables, for all households, fishing households, and non-fishing significantly different among the households sampled (t=−1. 98, p=0.05) households. Fishing and non-fishing households were compared using

Variable Range All households Fishing households Non-fishing (111 households) 38 (34 %) households 73 (66 %) n (%) or N (SD) n (%) or N (SD) n (%) or N (SD)

Food insecurity 0-moderate/severe insecurity 67 (60 %) 21 (55 %) 46 (63 %) 1-food secure/mild insecurity 44 (40 %) 17 (45 %) 27 (37 %) Fish consumption 0- rarely consumed 55 (50 %) 18 (47 %) 37 (51 %) 1-regularly consumed 56 (50 %) 20 (53 %) 36 (49 %) Monthly income (n=108)* KES 100–18,000 KES 3506 (48.5) KES 3292 (20.3) KES 3619 (40.60) USD $1.25–225 USD $43.82 ($0.61) USD $41.15 ($0.25) USD $45.24 ($0.51) Monthly income KES 100–31,000 KES 4258 (5530) KES 3292 (2618) KES 4748 (6493) USD $1.25–387.5 USD $53.22 ($69) USD $41.15 ($32.73) USD $59.35 ($81.16) Asset index 11 item scale 4.23 (1.78) 4.47 (1.99) 4.18 (1.66) Number in household 1–12 5.27 (2.40) 5.79 (2.24) 5 (2.46) Adult male 0-no male age 16 or older 24 (22 %) 0 (0 %) 24 (33 %) 1-at least one male age 16 or older 87 (78 %) 38 (100 %) 49 (67 %) Adult morbidity 0-never ill 49 (44 %) 12 (32 %) ** 37 (51 %) ** 1-male or female head of household too 62 (56 %) 26 (68 %) 36 (49 %) ill to work at least 1 day last month Male morbidity 0-never ill 53 (61 %) 17 (45 %) 36 (73 %) 1-male head of household too ill to work 34 (39 %) 21 (55 %) 13 (27 %) at least 1 day last month n=87

*Outliers were removed – three values from 30,000 to 31,000 KES were removed with validation by the inter-quartile range rule for outliers **p<0.05, Welch’s two-sample t-test for unequal variance consumption and morbidity. We found, however, no associa- do not eat more fish than their non-fishing neighbors. For tion between participation in fishing livelihoods and either many households around Lake Victoria, fish species and size fish consumption or food security. dictate whether a fish represents a “cash crop” or a food Although Lake Victoria has sufficient fish to feed an inter- resource. Complex political economies appear to separate national export market, fishers who regularly catch these fish fishing livelihoods from fish consumption while positioning

Table 2 Determinants of fish consumption and food security, all households (N=108). Odds ratios for bivariate models and adjusted odds ratios for full models. Models include all households and predict fish consumption (left) and food security (right)

Determinants of fish consumption Determinants of food security

Odds ratio (95 % confidence interval) Odds ratio (95 % confidence interval)

Determinant Bivariate p-value Full Model p-value Determinant Bivariate p-value Full Model p-value

Asset Index 1.47 0.003 −−Asset Index 1.52 <0.001 1.37 0.03 (1.14–1.88) (1.18–1.95) (1.04–1.82) Monthly Income (Log) 2.58 <0.001 2.40 0.001 Monthly Income (Log) 2.08 <0.01 1.67 0.04 ! (1.59–4.19) (1.45–3.98) (1.30–3.31) (1.02–2.74) 11 Number in Household 1.15 0.08 −−Number in Household 0.97 0.74 −− (0.98–1.36) (0.83–1.14) Education 1.33 0.09 −−Education 1.18 0.28 −− (0.96–1.84) (0.87–1.61) Fishing Household 1.18 0.69 −−Fishing Household 1.46 0.36 −− (0.53–2.59) (0.65–3.26) Food Security 1.22 0.01 1.18 0.04 Fish Consumption 2.60 0.02 −− (1.05–1.41) (1.00–1.39) (1.17–5.78) Adult Morbidity 0.47 0.054 0.48 0.10 Adult Morbidity 0.63 0.25 −− (0.22–1.01) (0.19–1.16) (0.29–1.38) Author's personal copy

K.J. Fiorella et al.

Variable Range All households Fishing households Non-fishing (111 households) 38 (34 %) households 73 (66 %) n (%) or N (SD) n (%) or N (SD) n (%) or N (SD)

Determinants of fish consumption Determinants of food security

Odds ratio (95 % confidence interval) Odds ratio (95 % confidence interval)

Determinant Bivariate p-value Full Model p-value Determinant Bivariate p-value Full Model p-value

Asset Index 1.47 0.003 −−Asset Index 1.52 <0.001 1.37 0.03 (1.14–1.88) (1.18–1.95) (1.04–1.82) Monthly Income (Log) 2.58 <0.001 2.40 0.001 Monthly Income (Log) 2.08 <0.01 1.67 0.04 (1.59–4.19) (1.45–3.98) (1.30–3.31) (1.02–2.74) Number in Household 1.15 0.08 −−Number in Household 0.97 0.74 −− (0.98–1.36) (0.83–1.14) Education 1.33 0.09 −−Education 1.18 0.28 −− (0.96–1.84) (0.87–1.61) Fishing Household 1.18 0.69 −−Fishing Household 1.46 0.36 −− (0.53–2.59) (0.65–3.26) Food Security 1.22 0.01 1.18 0.04 Fish Consumption 2.60 0.02 −− (1.05–1.41) (1.00–1.39) (1.17–5.78) Adult Morbidity 0.47 0.054 0.48 0.10 Adult Morbidity 0.63 0.25 −− (0.22–1.01) Author's(0.19–1.16) personal copy (0.29–1.38)

Fishing for food? Fishing livelihoods and food security

Table 3 Determinants of fish consumption and food security in households with adult males (N=84). Odds ratios for bivariate models and adjusted odds ratios for full models are reported. Models include only households with adult male members and predict fish consumption (left) and food security (right)

Determinants of fish consumption Determinants of food security

Odds ratio (95 % confidence interval) Odds ratio (95 % confidence interval)

Determinant Bivariate p-value Full Model p-value Determinant Bivariate p-value Full Model p-value

Asset Index 1.44 0.008 −−Asset Index 1.62 0.001 1.48 0.02 (1.10–1.88) (1.21–2.15) (1.07–2.04) Monthly Income (Log) 2.67 0.001 2.66 0.001 Monthly Income (Log) 2.87 0.001 2.16 0.02 (1.47–4.82) (1.46–4.84) (1.52–5.45) (1.12–4.18) Number in Household 1.12 0.25 −−Number in Household 1.05 0.61 −− (0.93–1.35) (0.87–1.29) Education 1.30 0.17 −−Education 1.18 0.35 −− (0.90–1.89) (0.84–1.66) Fishing Household 0.85 0.72 −−Fishing Household 0.95 0.60 −− (0.36–2.03) (0.79–1.15) Food Security 1.15 0.10 −−Fish Consumption 2.17 0.09 −− (0.97–1.37) (0.88–5.31) Adult Morbidity 0.44 0.072 −−Adult Morbidity 0.75 0.52 −− (0.18–1.08) (0.31–1.81) Male Morbidity 0.58 0.23 0.46 0.12 Male Morbidity 0.86 0.73 −− (0.24–1.39) (0.17–1.24) (0.34–2.09)

income as a key driver of both fish consumption and food Nile tilapia (Oreochromis niloticus) and dagaa (locally called security. Our findings may reflect a truly absent relationship, omena, Rastrineobola argentea). The focus of this research ISCUSSION 4.genderedD differences in fishing and food preparation, and/or was on Nile perch fishers and consumption. Access to alter- the limitations of our study to fully capture households’ live- native fish species, particularly dagaa, a sardine-like fish with Welihood found activities. consistent All of these associations potential causes among have food broad securitymore and limited fish international consumption export and potential socioeconomic but a prominent indicators,implications for as how well we as understand tentative the evidence connection of of liveli-a negativeplace association in the culinary between customs offish lakeside consumption communities, and may morbidity.hoods to food We security found, and natural however, resources. no association betweencontribute participation to fishers propensity in fishing to sell livelihoods rather than consumeand either fish consumption or food security. Nile perch. Fishing households, fish consumption and food security Although Lake Victoria has sufficient fish to feed anMorbidity international and fish consumption export market, fishers who There may be no association in this community between regularlwhether ay household catch these fishes fish for itsdo livelihoodnot eat more and fish fish con- thanOur their results non suggest-fishing a relationship neighbors. between For many fish consumption sumption or food security. Worldwide, the percentage of catch and morbidity that merits further research. For households retained by small-scale fishers ranges from nearly 100 % to with adult morbidity in the preceding month, the odds of !less than 20 % (Garaway 2005;Friedmanetal.2008; regular fish consumption are halved. Among households with12 Kawarazuka and Bene 2010). Around Lake Victoria, reports adult males, male rather than adult morbidity seems to drive suggest fishing households have higher mean incomes this relationship. High household morbidity may make it more (Allison 2004), but command only a fraction of the total value difficult for households to earn money or fish, and poverty, of the fish caught (Johnson 2010). The extensive export of low income, and low fish consumption make higher morbidity Nile perch has driven questions of whether food security is levels likely. HIV/AIDS prevalence, estimated at over 25 %, reconcilable with the exclusionary export market of Lake and endemic tropical diseases drive high levels of morbidity at Victoria and associations between the growth of the Nile the study site where 48 % of adult males were ill at least one Perch fishery and local hunger (Abila 2003; Geheb et al. full day during the last month and 21 % were ill for a week or 2008; Johnson 2008; Salmen 2009). more. Both the reported frequency of illness and the large As demonstrated in our results, income may overwhelm number of households headed by grandparents or without an fishery participation as the driver of fish consumption. This adult male reflect extensive morbidity and mortality. The result is corroborated by reports of people living around Lake possible association between fish consumption and morbidity Victoria sometimes being relegated to consumption of low warrants further study of the pathways through which mor- value fish and by-products from processing (Kabahenda et al. bidity affects fishers’ ability to catch fish, or consume their 2011). In Lake Victoria, there are currently three primary catch. At the same time, the impact of morbidity on food species fished and consumed: Nile perch (Lates niloticus), insecurity may have cyclical effects on economic and health households around Lake Victoria, fish species and size dictate whether a fish represents a “cash crop” or a food resource. Complex political economies appear to separate fishing livelihoods from fish consumption while positioning income as a key driver of both fish consumption and food security. Our findings may reflect a truly absent relationship, gendered differences in fishing and food preparation, and/or the limitations of our study to fully capture households’ livelihood activities. All of these potential causes have broad implications for how we understand livelihoods connection to food security and natural resources.

Fishing Households, Fish Consumption and Food Security

There may, in fact, be no association in this community between whether a household fishes for its livelihood and fish consumption or food security. Worldwide, the percentage of catch retained by small-scale fishers ranges from nearly 100% to less than one fifth (Garaway 2005; Friedman K 2008; Kawarazuka and Bene 2010). Around Lake Victoria, reports suggest fishing households have higher mean incomes (Allison 2004), but command only a fraction of the total value of the fish caught (Johnson 2010). The extensive export of Nile perch has driven questions of whether food security is reconcilable with the exclusionary export market of Lake Victoria and to associate the growth of the Nile Perch fishery with local hunger (Abila 2003; Geheb et al. 2008; Johnson 2008; Salmen 2009).

As demonstrated in our results, income may overwhelm fishery participation as the driver of fish consumption. This result is corroborated by reports of people living around Lake Victoria sometimes being relegated to consumption of low value fish and by-products from processing (Kabahenda et al. 2011). In Lake Victoria, there are currently three primary species fished and consumed: Nile perch (Lates niloticus), Nile tilapia (Oreochromis niloticus) and dagaa (locally called omena, Rastrineobola argentea). The focus of this research was on Nile perch fishers and consumption. Access to alternative fish species, particularly dagaa, a sardine-like fish with more limited international export potential but a prominent place in the culinary customs of lakeside communities, may contribute to fishers propensity to sell rather than consume Nile perch.

Morbidity and Fish Consumption

Our results suggest a relationship between fish consumption and morbidity that merits further research. For households with adult morbidity in the preceding month, the odds of regular fish consumption are halved. Among households with adult males, male rather than adult morbidity seems to drive this relationship. High household morbidity may make it more difficult for households to earn money or fish, and poverty, low income, and low fish consumption make higher morbidity levels likely. HIV/AIDS prevalence, estimated at over 25%, and endemic tropical diseases drive high levels of morbidity at the study site where 48% of adult males were ill at least one full day during the last month and 21% were ill for a week or more. Both the reported frequency of illness and the large number of households headed by grandparents or without an adult male reflect extensive morbidity and mortality. The possible association between fish consumption and morbidity warrants further study of the pathways through which morbidity affects fishers’ ability to catch fish, or consume their catch. At the same time, the impact of morbidity on food insecurity may have cyclical effects on economic and health decision making, potentially leading to increased risk of HIV acquisition (Mojola 2011).

! 13

Socioeconomic Associations With Fish Consumption and Food Security

An increase in monthly income was associated with 2.40-2.67 times the odds of high fish consumption compared to low fish consumption and 1.67-2.18 the odds of food security compared to moderate or severe food insecurity. The relatively strong association between income and food security is expected, given established relationships between income and food security (Geheb and Binns 1997). These associations exist despite the narrow range of income levels represented in the study, suggesting that even modest improvements in income could substantially improve food security or fish consumption. Ninety five percent of households reported a monthly income under 12,000KES ($150), or less than $1/person/day given the mean household size of 5 members. Even within this narrow range, modest increases in income were associated with meaningful increases in fish consumption and food security.

The asset scale, another measure of socio-economic status, is retained in models for associations with food security, but not fish consumption. The relative strength of the association between fish consumption with monthly income, indicative of short-term socio-economic status, compared to assets which is reflective of long term financial security, further suggests that fish may largely be procured through purchase rather than associated with particular livelihoods.

Measuring Livelihoods and Study Limitations

A livelihood comprises a household’s capabilities and means of living, including its access to food (Chambers and Conway 1992). A household’s livelihood is challenging to measure, and our analysis has several limitations. We accounted for only the main ways that households earn an income or the occupation that defines each individual. Consequently, we could not examine the role of subsistence fishing in food security and fish consumption, and could not capture information about illegal fishing, fishing by children, and other methods of obtaining fish, all of which likely remain important ways households access fish (LVFO 2012). Similarly, we were unable to account for the effort each household puts into fishing or women’s engagement in selling and processing fish, non-fishing livelihoods that interact with fish. Further analysis explicitly considering gendered vantage points in decision-making and accessing fish would expand our understanding of how food-producing livelihoods interact with consumption and food security.

Gendered differences in livelihoods and household responsibilities also likely affect whether households consume fish. In Lake Victoria, the harvest of fish, and of Nile perch in particular, remains a male-dominated activity (Geheb et al. 2008; Nadel-Klein and Davis 1988). Yet, women remain broadly responsible for procuring food, preparing meals, and budgeting for these activities; decisions about whether to sell fish or bring them home for dinner are often made by men, without the immediate counsel of their partners (Whyte and Kariuki 1991). The gendered nature of fishing and food preparation may also drive a disconnect between fishing livelihoods and consumption in these communities.

The cross-sectional nature of our study limits our ability to make causal inferences regarding the observed associations. In particular, the absence of temporality makes it difficult to distinguish

! 14 whether fish consumption or food security precedes the other. Further, our study was not powered to detect small differences between fishing and non-fishing households, and these may exist.

5.CONCLUSION

Livelihood strategy has implications for both how households use fishery resources and how patterns of use are related to income, food security, and morbidity (de Sherbinin et al. 2008). That we saw no effect of household engagement in fishing on their consumption of fish or on food security suggests that the complexity of these relationships demands a more rigorous and ideally longitudinal study. Additional research is needed to assess seasonal changes, gendered effects of participation in the livelihood, and relative differences in household investment and success in the livelihood activities. Moreover, the frameworks with which we evaluate interventions to improve livelihoods and assess their effects on food security, dietary consumption, nutritional status, and morbidity face similar challenges in accounting for livelihoods within complex political economies. Food, as a biological necessity, cultural symbol, and economic resource, remains Author'sliterally at the personal center of householdcopy wellbeing for rural communitiesFishing for food? Fishing around livelihoods the andglobe. food security By further untangling the lines that lead from the fish net to the plate, we can design better measures to assess relationships between food production and food UCB Global Health Framework Program, which was funded by grant Dean’s Research Fellowship (to JMN); UCSF PACCTR and Global security,5R25TW7512-3 and from better the National target Institutes effective of Health livelihood (NIH)/Fogarty interventionsHealth Pathways for Research poor Programfamilies (to CRS).who Thisneed study them is published most.International Center. This work was partly supported by NSF-GEO grant with the permission of the Director, KEMRI. CNH115057; an Andrew and Mary Thompson Rocca Pre-dissertation Fellowship, Sara’s Wish Foundation, National Science Foundation Grad- uate Research Fellowship Program (to KJF); Doris Duke Charitable Conflict of interest The authors declare that they have no conflicts of Foundation International Clinical Research Fellowship (to MDH); UCSF interest.

Appendix

Table 4 Variable definitions and references

Variable Type Definition Reference

Fishing Household Binary Occupation designated as fisher Nile perch or tilapia fishing designated as a primary income-earning activity Food Security Binary Moderate and severe food insecurity categories: frequency of any Household Food Insecurity Access Scale household member taking smaller meals, fewer meals, go to sleep – Q5, 6, 8, 9 (Coates et al. 2007) hungry, go a whole day and night without eating Fish Consumption Binary Frequency of household fish or meat consumption; ethnographic experience confirms meat consumption is extremely rare Income Continuous Past month’s income Asset Scale Categorical 11-item asset scale Asset scale (Vyas and Kumaranayake 2006); Ethnographic Research (Salmen 2009) Household Size Categorical Number of members in the household, binned at upper end Education Categorical The highest level of maternal education attained; recorded as some primary, primary, some secondary, etc. Adult Morbidity Binary Characterizes whether an adult household member (≥16 years) was too sick to attend work or school at least 1 day in the past month Male Morbidity Binary Characterizes whether an adult male household member (≥16 years) was too sick to attend work or school at least 1 day in the past month

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! 16 Girard, A. W., Self, J. L., McAuliffe, C., & Olude, O. (2012). The Effects of Household Food Production Strategies on the Health and Nutrition Outcomes of Women and Young Children: A Systematic Review. Paediatric and Perinatal Epidemiology, 26, 205-222. Johnson, J. (2008). Of Darwin's Dreams and Nightmares: The Concelaed Violence of a Global Whitefish Commodity. University of Michigan, Ann Arbor, Michigan. Johnson, J. L. (2010). From Mfangano to Madrid: The global commodity chain for Kenyan Nile perch. Aquatic Ecosystem Health & Management, 13(1), 20-27. Kabahenda, M. K., Amega, R., Okalany, E., Husken, S. M. C., & Heck, S. (2011). Protein and Micronutrient Composition of Low-Value Fish Products Commonly Marketed in the Lake Victoria Region. World Journal of Agricultural Sciences, 7(5), 521-526. Kawarazuka, N., & Bene, C. (2010). Linking small-scale fisheries and aquaculture to household nutritional security: an overview. Food Security, 2(4), 343-357. Kenya Ministry of Health (2013). Kenya County HIV Service Delivery Profiles. Republic of Kenya: Ministry of Health. Kenya National Bureau of Statistics and ICF Macro (2010). Kenya Demographic and Health Survey 2008-09. Calverton, Maryland: KNBS and ICF Macro. Kumar, N., & Quisumbing, A. R. (2010). Access, Adoption, and Diffusion: Understanding the Long-term Impacts of Improved Vegetable and Fish Technologies in Bangladesh. In H. Poverty, and Nutrition Division (Ed.), IFPRI Discussion Paper 00995: International Food Policy Research Institute. LVFO (2012). Regional Frame Survey Report. Regional Status Report on Lake Victoria Bi- ennial Frame Surveys Between 2000 and 2012. Kenya, Tanzania, and Uganda: Lake Victoria Fisheries Organization. Milner-Gulland, E. J., Bennett, E. L., & Meat, S. C. B. A. m. W. (2003). Wild meat: the bigger picture. Trends in Ecology & Evolution, 18(7), 351-357. Mojola, S. (2010). Fishing in dangerous waters: Ecology, gender and economy in HIV. Social Science and Medicine, 72(2), 149-156. Nadel-Klein, J., & Davis, D. L. (1988). Introduction: Gender in the maritime arena. In J. Nadel- Klein, & D. L. Davis (Eds.), To work and to weep. Newfoundland: Memorial University. Nagata, J. M., Fiorella, K. J., Young, S. L., Otieno, O. D., Kapule, I., Bukusi, E. A., et al. (2013). Socio-demographic and health associations with body mass index at the time of enrollment in HIV care in Nyanza Province, Kenya. AIDS Care, 1-8. Nagata, J. M., Magerenge, R. O., Young, S. L., Oguta, J., Weiser, S. D., & Cohen, C. R. (2012). 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, 24(6), 728-736. Njiru, M., Nzungi, P., Getabu, A., Wakwabi, E., Othina, A., Jembe, T., et al. (2007). Are fisheries management, measures in Lake Victoria successful? The case of Nile perch and Nile tilapia fishery. African Journal of Ecology, 45(3), 315-323. Pauly, D., Watson, R., & Alder, J. (2005). Global trends in world fisheries: impacts on marine ecosystems and food security. Philosophical Transactions of the Royal Society B- Biological Sciences, 360(1453), 5-12. Salmen, C. (2009). Towards an Anthropology of Organic Health: The Relational Fields of HIV/AIDS among the Suba of Lake Victoria. Oxford University, Stata (1985-2011). Stata Statistics/Data Analysis. (Vol. 12.1). College Station, Texas, USA: StataCorp LP.

! 17 Talman, A., Bolton, S., & Walson, J. L. (2012). Interactions Between HIV/AIDS and the Environment: Toward a Syndemic Framework. American Journal of Public Health, 103(2), 253-261. Vyas, S., & Kumaranayake, L. (2006). Constructing socio-economic status indices: how to use principal components analysis. Health Policy and Planning, 21(6), 459-468. Whyte, S. R., & Kariuki, P. W. (1991). Malnutrition and Gender Relations in Western Kenya. Health Transitions Review, 1(2). Witte, F., Goldschmidt, T., Wanink, J., Vanoijen, M., Goudswaard, K., Wittemaas, E., et al. (1992). The Destruction of an Endemic Species Flock - Quantitative Data on the Decline of the Haplochromine Cichlids of Lake Victoria. Environmental Biology of Fishes, 34(1), 1- 28.

! 18 Chapter 3. Fish Availability and Household Fish Consumption

1. INTRODUCTION

While ecosystem function and human well-being have been closely linked, the mechanisms through which natural systems interact with livelihoods and human health are most often examined quantitatively only at global and regional scales (Corvalán et al. 2005). Yet local interactions between people and the environment drive the ways households and individuals respond to environmental change. Nowhere is this reliance more critical than for the 47% of the global population living in rural areas and reliant on natural resources to provide for food and livelihoods (World Bank 2013). The preponderance of households reliant on natural resources live in economically developing countries, where they are on the frontlines of global environmental change while coping the highest burdens of malnutrition and poverty.

While much research has sought to understand household reliance on natural resources, integrating the dynamics of ecosystems that provision resources and feed back to affect household behavior adds a new dimension to this work (Carter et al. 2014). Efforts to understand coupled human and natural systems, also termed socio-ecological systems and socio-environmental systems, provides for an interdisciplinary integration of the dynamics of natural resources and social systems (Liu et al. 2007b; Ostrom 2009; Walker et al. 2004). Such an integration provides for new insights into the complexity and dynamism of these systems (Liu et al. 2007a; Schlueter et al. 2012) and integrally extends understandings of human-environment interactions beyond appreciating changes in household demographic trends (Hummel et al. 2013; Liu et al. 1999).

The integration of human and natural systems at a household level creates substantial challenges for bounding inquiries in time and space. The scale at which natural resources available to households affect their consumption is altered by factors as diverse as the distance people travel to access resources, the effects of harvest on regional prices, or the length of time food is stored. Both influenced by the broader context and inherent to individual households, the time and space bounds of resource utilization dictate the scale at which changes in resource availability affect households. Appreciating the scale of these influences is critical to understand the reverberations of changing resource availability within households and the consequences for dietary consumption and future resource use.

We aim here to analyze a range of scales – both of resource availability and resource consumption – in a Kenya fishery. Using the case of Lake Victoria, we analyze the scale at which changing fish availability impacts fish consumption in local households. In assessing the scale of resource availability, we consider the influence of different metrics of fish availability, including fish catch, fishing effort, and prices. We consider, also, the time scales that affect these metrics over the previous month, week and days. In assessing the scale of household use of fish resources, we assess metrics of the quantity and frequency with which fish is consumed. Our analysis provides insight into the relevant boundaries of fish availability and the scale at which changes in fish access may affect household consumption of fish resources and, thereby, the nutrition of household members.

! 19 2. METHODS

Study Site

We conducted this study on Mfangano Island, located within Homa Bay County in Nyanza Province, Kenya. A continental island in Lake Victoria, Mfangano is approximately 65km2 and home to 21,000 people (Mbita Division 2009). Fishery involvement, both for trade of fish and subsistence use, is widespread (Fiorella et al. 2014). Mfangano has limited health infrastructure and electricity, and no running water or paved roads. Food insecurity is common throughout Mfangano and ubiquitous among people living with HIV/AIDS (Nagata et al. 2012; Nagata et al. 2013; Nagata et al. 2014; Fiorella et al. 2014). HIV prevalence is over 25% among adults (Kenya Ministry of Health 2013).

Household Survey Methods

Data were collected from December 2012 – March 2013 and are a subset of a larger study of fishing livelihoods, fish consumption and child nutrition. Household data include 4 time points – baseline, 3-months, 6-months and 12-months – selected to capture both seasonal fishery variation and growth and cognitive development of children <2 years of age. Data were collected for 303 participant households randomly selected from an enumerated sampling list of all households with a child <2 years of age and living on Mfangano Island, Kenya. Eight households had twins, and these household characteristics are included for each child in the study. Local enumerators conducted surveys in Dholuo, the local language. We obtained written consent from study participants prior to enrollment.

Household food security was measured by the 9-item Household Food Insecurity Access Scale, for which standardized categories and scores were calculated (Coates et al. 2007). Fish consumption was determined by maternal recall of fish prepared for the household, the method by which the fish was procured, and consumption of the fish by herself and her child. The household mother provided Demographic and Income characteristics. Principal components analysis was used with a scale of furniture ownership (e.g. bed, bureau, couches) to generate a measure of household assets with principal component 1 (eigenvalue=2.36). Food security, fish consumption, demographic and income questionnaires were administered to the household mother. Where families were polygamous, a household headed by each co-wife was surveyed separately.

We summarize variables and characteristics across all households and timepoints of data collection before focusing on a subset of households living on Takawiri Island (n=35) for comparisons among patterns of fish consumption and fish availability.

The study protocol was reviewed and approved by the University of California, Berkeley Committee on Human Research and the Ethical Review Committee of the Kenya Medical Research Institute. We omit names of individuals, beaches, and villages to protect the confidentiality of study participants.

! 20 Fishery Data Collection

Fishery data was collected in collaboration with the Kenya Ministry of Fisheries Development and Mfangano’s 19 local Beach Management Units. The Beach Management Units provided daily data on fish catch, prices, and effort by each boat from February 12, 2013 to October 12, 2014. Fishery data was limited to those Nile perch that were of legal catch size and sold through the Beach Management Unit structure. The availability of these fish form a proxy for catch of small size Nile perch and an analog to catch of dagaa, both of which are also fished and consumed locally without a formal data collection mechanism.

Fishery data presented here are restricted to a single Beach Management Unit and are recorded on 75% of weekdays, or 54% of days in the 21-month range, despite a substantial break in data collection over December 2013 to January 2014. Average catch, catch/boat, price, and number of boats fishing were computed for each date for the preceding 30 days, 7 days, and 3 days for comparison with fish consumption data. These averages were available for 93%, 77% and 63% of dates, for 30, 7, and 3-day periods, respectively.

Statistical Analyses

For all households, differences in demographic characteristics and household food security, household fish consumption, and child nutritional status across time points are compared using Pearson Chi^2 tests. In addition, characteristics of fish consumption, including fish types, frequency of consumption, and households’ methods of procuring fish (e.g. purchase, fishing, trading), are tabulated.

Over time, fishery catch at a single Beach Management Unit are compared based on monthly fish catch, catch per unit effort (kg/boat), number of boats, and rate (KES/kg).

To assess the contribution of fish availability to fish consumption, we compare panel data univariate regression models for these metrics – total fish catch, catch per unit effort (kg/boat), and rate (KES/kg) – over the previous 30, 7, and 3 days to household variables of fish consumption. These models control for household and time point through the inclusion of fixed effects. Household variables of consumption are summed across 3 days and include (a) consumption, of any fish, Nile perch, omena, or other fish types; (b) quantity of fish consumed, Nile perch and omena; (c) quantity consumed per meal, Nile perch and omena; and (d) number of fish meals eaten by particular household members, women and young child.

3. RESULTS

Descriptive statistics for all households, by time point, are presented in Tables 1 and 2. While demographic characteristics of study households do not change substantially between baseline and the 12-month time point (Table 1), we observe differences in outcome variables of food security, fish consumption, and child nutritional status (Table 2) across time points. The main maize harvest in August, appears to influence household food security, with a reduction in severe food insecurity observed around and following the harvest. However, year round, a substantial

! 21 number of households remain severely food insecure (45-67%, across time points). Fish is an important food source, providing an average of 2.1-2.5 meals over the previous three days. Further, as the cohort of children ages from 12.2 to 24.1 months, rates of moderate wasting decrease from 5% to 3% while moderate stunting rates increase from 19% to 32%.

Household fish consumption, by fish sizes and attainment methods, is detailed in Table 3. Household reports of fish consumption over the three prior days at each time point provide for details of 3,329 fish meals. The majority of these meals (51%) were dagaa (Rastrineobola argentea), a small sardine-like fish, with the fish purchase 84% of the time. Nile perch (Lates niloticus) comprised 39% of meals, across different size classes, the majority of which were juvenile Nile perch (90%). Across size classes, 44-64% of Nile perch were bought, and 29-54% were caught. Once substantial parts of the Lake Victoria fishery, tilapia (Oreochromis niloticus) and cichlids (Haplochromis) comprised just 4% and 1% of fish meals, with other native species providing 1% as well.

Using the restricted fishing data, yield and effort for a single Beach Management Unit is averaged across each month to provide catch per unit effort (kg/boat), number of boats fishing, rate (KES/kg) and daily catch (kg) (Figure 1). Catch per unit effort, number of boats fishing and daily catch variables follow a similar pattern with depressed effort and catch in July-August when fish are less available and efforts are diverted to farm harvests. This pattern, however, is more pronounced in 2014 than 2013. Fluctuations in average daily catch ranged from 74.4kg to 592.5kg with the average number of boats fishing ranging from 17.2 to 55.8 boats. Finally, the catch per boat, ranged from 3.3 kg/boat to 12.3 kg/boat. In contrast, the rate for a kilogram of fish has doubled from a low of 119 KES/kg, or $1.48/kg in March 2013 to rates exceeding 240 KES/kg or $3/kg after September 2014.

Comparing households within the catchment of the restricted fishery data (n=36), we use a series of univariate regression models to examine the associations between different metrics of fish availability (catch/boat, catch, and rate) and time frames (previous 30, 7 and 3 days) to a range of metrics of household fish consumption over the previous 3 days (meals, quantity, quantity/meal, consumer) (Table 4). Comparisons among regression results reveal similar patterns across shorter time frames (3 and 7 days) for the effects of catch and catch per boat on consumption. The effects of rate, in contrast, diverge from catch metrics and are more similar across longer time frames (7 and 30 days). Metrics of quantity of fish and consumer appear to provide more nuanced perspectives on household fish consumption.

! 22 Table 1: Household demographic characteristics, at Baseline and 12 months. Pearson Chi^2 tests are used to assess whether these characteristics differ at Baseline and 12 months.

12 months Pearson Timepoint Baseline (n=311) (n=275) chi2 n/mean %/SD n/mean %/SD Married 275 88% 241 87% 0.907 Marital Status Widowed 23 7% 23 8% Other 13 4% 11 4% Some Primary 158 51% 108 39% 0.145 Maternal Primary 93 30% 101 37% Education Some Secondary 31 10% 38 14% Secondary or higher 24 8% 27 10% Age (yrs) 27.4 6.5 28.3 7% 0.109 Under 20 28 11% 14 5% Maternal Age 20-29 164 61% 164 61% 30-39 64 24% 76 28% Over 40 11 4% 14 5% less than 4 31 10% 31 11% 0.895 4 54 17% 46 17% 5 68 22% 57 21% Household Size 6 63 20% 56 20% 7 40 13% 41 15% 8 27 9% 25 9% over 9 27 8.7 19 7% 2860. 2556. Assets & Food Expenditures 5082.5 5 4898.4 9 --- Expenditures Furniture Index 0-4 1.9 0.95

! 23 Table 2: Household food security, fish consumption, and child nutritional status across time points. At each time point, scores and categories are presented for household food security and fish consumption over the last three days. In addition, Z scores for child nutritional status referencing the WHO growth curves for stunting and wasting are included. Pearson Chi^2 tests are used to assess whether these characteristics differ across time points.

Baseline 3 months 6 months 9 months 12 months Timepoint Jan-Mar 2013 Apr-Jun Jul-Sep Oct-Dec Jan-Mar 2014 Pearson n/mean %/sd n/mean %/sd n/mean %/sd n/mean %/sd n/mean %/sd chi2 n 311 290 281 274 275 Score (range: 9-36) 18.4 5.0 17.9 4.6 17.1 4.4 17.3 4 17.2 4.5 Household Secure 13 4% 12 4% 20 7% 11 4% 10 4% 0.000 Food Mild Insecure 21 7% 17 6% 23 8% 13 5% 25 9% Security Mod. Insecure 70 22% 92 31% 112 40% 121 44% 89 32% Sev. Insecure 208 67% 174 59% 126 45% 129 47% 154 55% Fish Meals (last 3 days) 2.4 1.0 2.5 0.81 2.3 0.9 2.5 0.8 2.1 0.8 Household 1 50 16% 27 9% 47 17% 29 11% 61 22% 0.000 Fish 2 111 36% 113 39% 122 43% 105 38% 117 43% Consumption 3 107 35% 119 41% 88 31% 114 42% 74 27% over 3 35 11% 27 9% 23 8% 19 7% 13 5% Child Age (months) 12.2 7.1 15.8 7.1 18.4 7.1 20.8 7.1 24.1 7.1 Height/Length -1.05 1.30 -1.26 1.30 -1.23 1.30 -1.49 1.18 -1.49 1.28 for Age Z score < -2 60 19% 74 26% 64 23% 88 32% 88 32% 0.001 (Stunting) Z score < -3 22 7% 24 8% 17 6% 20 7% 24 9% 0.800 Weight for 0.07 1.24 0.08 1.25 0.06 1.06 0.32 1.02 0.28 1.07 Height/Length Z score < -2 14 5% 15 5% 7 2% 3 1% 7 3% 0.043 (Wasting) Z score < -3 5 2% 6 2% 1 0% 0 0% 1 0% 0.036

! 24 Table 3: Types of fish consumed and methods of obtaining fish. The number and proportion of meals consumed of different fish types and sizes and the method through which participants reported obtaining the fish consumed. Households reported all fish meals over the previous 3-day period at each of 5 time points over the course of a year.

Legal Attainment method Fish Type Total Meals Catch Bought Caught Shared Other Nile perch, very small (<.5kg) N 14 0.4% 9 64% 4 29% 0 0% 1 7% 100 Nile perch, small (.5-.75kg) N 8 30% 609 60% 364 36% 32 3% 3 0% Nile perch, ‘undersized’ (.75-1kg) N 159 5% 70 44% 86 54% 3 2% 0 0% Nile perch Y 125 4% 62 50% 54 43% 5 4% 4 3% Tilapia (small) N 35 1% 18 51% 16 46% 1 3% 0 0% Tilapia Y 113 3% 59 52% 51 45% 2 2% 1 1% 168 Dagaa Y 6 51% 1420 84% 195 12% 67 4% 4 0% Cichlid NA 169 5% 102 60% 30 18% 24 14% 13 8% Other* NA 20 1% 10 50% 9 45% 1 5% 0 0% 332 TOTAL 9 100% 2359 71% 809 24% 135 4% 26 1% *Mumi, Suma, Mamba, Okoko !

! 25 ! ! ! ! Average Fishing Yield and Effort CPUE (kg/boat)

Boats Fishing

Rate (KES/kg)

Catch (kg)

! Figure! 1: Average monthly fishing catch and effort. Average (a) catch per unit effort (CPUE, catch/boat) and number of boats fishing and (b) rate (KES/kg) and catch (kg) from February 2013 to October 2014. Bars represent standard deviations based on the averaging of daily values.

! 26 Table 4: Comparisons of different measures of fish availability (Catch/Boat, Total Catch, Rate) and time frames (previous 30, 7 and 3 days) to measures of household fish consumption (meals, quantity, quantity per meal, and consumer). All results shown are univariate logistic regressions where the metric of fish availability is the predictor of household fish consumption, the outcome variables. Results shown in bold have a p value <0.05.

5 kg Catch / Boat Total Catch (100 Kg) Rate ($) Coef SE p 95% CI Coef SE p 95% CI Coef SE p 95% CI Outcome variable Last 30 Days Any fish -0.10 0.18 0.57 -0.45 0.25 -0.07 0.06 0.22 -0.19 0.04 -0.18 0.15 0.23 -0.46 0.11 Consumed Nile perch -0.19 0.16 0.22 -0.50 0.12 -0.09 0.05 0.09 -0.19 0.01 -0.01 0.14 0.96 -0.27 0.26 (# meals) Omena 0.13 0.13 0.32 -0.13 0.39 0.05 0.04 0.28 -0.04 0.13 -0.31 0.11 0.00 -0.53 -0.10 Other 0.02 0.19 0.90 -0.36 0.40 0.02 0.06 0.70 -0.10 0.15 -0.28 0.13 0.03 -0.54 -0.03 Nile perch (kg) 0.16 0.12 0.20 -0.08 0.40 0.06 0.04 0.17 -0.02 0.14 -0.29 0.10 0.01 -0.50 -0.09 Quantity Omena (bowls) 0.14 0.28 0.62 -0.41 0.69 0.04 0.09 0.70 -0.15 0.22 -0.69 0.24 0.00 -1.16 -0.23

Quantity per Nile perch -0.14 0.28 0.62 -0.70 0.41 -0.05 0.11 0.62 -0.26 0.16 0.19 0.25 0.44 -0.30 0.69 meal Omena bowls -0.14 0.10 0.15 -0.33 0.05 -0.06 0.03 0.07 -0.12 0.00 0.06 0.09 0.55 -0.13 0.24

Consumer Child -0.12 0.46 0.79 -1.02 0.78 -0.19 0.13 0.14 -0.45 0.06 0.39 0.62 0.54 -0.83 1.61 (# meals) Mother -0.83 0.35 0.02 -1.52 -0.15 -0.34 0.10 0.00 -0.52 -0.15 -0.10 0.49 0.83 -1.05 0.85 Last 7 Days Any fish -0.13 0.12 0.27 -0.37 0.10 -0.06 0.04 0.09 -0.14 0.01 -0.08 0.15 0.57 -0.37 0.20 Consumed Nile perch -0.13 0.11 0.23 -0.34 0.08 -0.04 0.03 0.20 -0.11 0.02 -0.04 0.14 0.77 -0.31 0.23 (# meals) Omena 0.01 0.09 0.94 -0.17 0.18 0.00 0.03 0.96 -0.05 0.06 -0.28 0.10 0.00 -0.48 -0.09 Other 0.05 0.18 0.78 -0.30 0.40 0.05 0.05 0.32 -0.05 0.16 -0.24 0.14 0.08 -0.51 0.03 Quantity Nile perch (kg) 0.09 0.09 0.33 -0.09 0.26 0.04 0.03 0.16 -0.02 0.09 -0.20 0.11 0.07 -0.41 0.02 Omena (bowls) -0.17 0.21 0.42 -0.57 0.24 -0.06 0.07 0.35 -0.19 0.07 -0.58 0.24 0.01 -1.05 -0.12

Quantity per Nile perch -0.02 0.18 0.92 -0.37 0.34 -0.01 0.07 0.90 -0.14 0.12 0.27 0.24 0.26 -0.20 0.73 meal Omena bowls -0.17 0.08 0.03 -0.32 -0.02 -0.06 0.02 0.01 -0.11 -0.01 0.07 0.09 0.44 -0.11 0.25

Consumer Child -0.12 0.29 0.68 -0.68 0.44 -0.06 0.07 0.38 -0.19 0.07 0.10 0.46 0.82 -0.79 1.00 (# meals) Mother -0.47 0.20 0.02 -0.87 -0.07 -0.14 0.05 0.00 -0.24 -0.05 0.09 0.34 0.79 -0.57 0.75 Last 3 Days Any fish -0.03 0.11 0.78 -0.24 0.18 -0.03 0.04 0.43 -0.10 0.04 -0.28 0.19 0.16 -0.66 0.10 Consumed Nile perch -0.13 0.09 0.16 -0.31 0.05 -0.04 0.03 0.20 -0.11 0.02 -0.01 0.19 0.94 -0.39 0.37 (# meals) Omena -0.01 0.08 0.87 -0.17 0.14 0.00 0.03 0.92 -0.06 0.05 -0.21 0.15 0.16 -0.50 0.08 Other -0.01 0.15 0.97 -0.31 0.30 0.03 0.05 0.63 -0.08 0.13 -0.43 0.25 0.08 -0.91 0.06 Quantity Nile perch (kg) 0.10 0.08 0.19 -0.05 0.25 0.04 0.03 0.18 -0.02 0.09 -0.21 0.16 0.19 -0.53 0.10 Omena (bowls) -0.16 0.19 0.40 -0.55 0.22 -0.06 0.07 0.40 -0.20 0.08 -0.77 0.35 0.03 -1.45 -0.09

Quantity per Nile perch -0.03 0.15 0.86 -0.33 0.28 -0.03 0.06 0.63 -0.15 0.09 0.72 0.29 0.01 0.14 1.29 meal Omena bowls -0.13 0.07 0.05 -0.26 0.00 -0.06 0.02 0.01 -0.11 -0.01 -0.02 0.13 0.85 -0.28 0.23

Consumer Child -0.36 0.34 0.29 -1.02 0.31 -0.10 0.09 0.22 -0.27 0.06 0.01 1.10 1.00 -2.15 2.16 27 (# meals) Mother -0.42 0.23 0.07 -0.88 0.03 -0.14 0.06 0.02 -0.25 -0.02 -0.69 0.80 0.38 -2.25 0.87

! 4. DISCUSSION

In considering the scale of resource availability that is relevant to household consumption, our results indicate that both fish and income within the community are acutely relevant to household fish consumption. Where households rely on natural resources for both food and income, these dynamics are likely to be intertwined in their influence on how resources are used. Within our study site, the majority of fish are purchased, rather than retained from the days’ catch. Consequently, overall fish availability and prices, as well as the degree to which households, and particularly women, have cash to purchase fish substantially shapes fish consumption. Of course, income in this community is largely shaped by fish catch, meaning that fish availability leads to household consumption through two pathways. The first pathway goes from fish catch directly to fish consumed, while the second passes from fish catch to income and then to fish purchased for home consumption.

The durability of fish and fishing income in households thus determines the time frame and metrics by which fish availability affects household fish consumption. Despite preservation techniques, such as drying and smoking, fish has a relatively short shelf life. Further, fishing income, where most households do not have substantial mechanisms for saving and experience relatively high food insecurity, may also have a relatively short durability. Further complicating the dynamics of availability and consumption, the widespread reliance on Nile perch as a key source of income, but dagaa as the predominate source of fish meals suggests the conversion of Nile perch availability into dagaa consumption. A similar pattern is suggested by metrics of fish availability and household fish consumption.

In considering the time frames of fish availability, our results suggest the relative short term durability of fish catch and effort, with longer range influences of fish price. Patterns of average fish catch and average fish catch per unit effort are consistent within 3 and 7 days of consumption bear out the relatively short durability of these resources’ availability. Thus, the shorter time frames provided by the 3 days matching the days over which household consumption is measured or the previous week metrics offer the most reliable assessments of household consumption. For fish prices, the rate paid for fish predicts consumption more consistently across longer time frames, suggesting the durability of cash in predicting consumption may be more reliable over 7 or 30 days.

The different metrics of assessing fish availability – total catch and catch per boat – provide for very similar patterns of fish catch. As seen in the monthly averages of these metrics, they track closely with effort and catch closely tied. Similarly, these metrics have commensurate influences on household fish consumption. Rate, a variable which steadily increases over the course of the study, however, has a different pattern of influences over fish consumption.

Metrics of fish consumption, though limited by a constrained sample size, indicate that fish availability influences consumption of fish, quantities consumed, and which household members consume fish. While mothers consumed fish 90% of the time when a fish meal was served, children consumed fish only 70% of the time a fish meal was served (inclusive of only children>6 months and eating family foods). Although our ability to disentangle the specific

! 28 influence of fish availability on consumption is limited by the restricted sample size, patterns of Nile perch availability influencing consumption of dagaa appear likely.

Limitations

Though our restricted sample allows for the observation of patterns and deviance, it provides for limited power and reliability in detecting the scale and direction of fish availability influences on fish consumption. Further, our analysis relies on multiple comparisons, suggesting that signficant findings in this work are likely to be the result of bias.

Finally, this work limits measurements of fish availability to the predominant Nile perch fishery. We thus make assumptions about the degree to which Nile perch availability predicts fish availability. In some instances, these assumptions are likely correct, for example, when weather or seasonal patterns influence fishing effort and thereby catch. However, fishers decisions to switch effort between target species and that declining Nile perch catch may drive increasing dagaa availability – both through ecological mechanisms that increase dagaa productivity and shifting fishing effort – complicate this assumption.

5. CONCLUSION

Understanding the scales and timeframes through which resource access shapes human use of natural resources, consumption, and well-being is critical to appreciating the links between human and natural systems. In particular, understanding the influences of changing environments, human adaptation, and management policies hinges on the degree to which we can measure relevant changes in natural resources. Assessing the geographic scales, time frames, harvest metrics, and pathways through which humans and environments interact are necessary to developing such measures of relevant changes.

We must understand, in particular, the influence of environmental change on the households that rely on resources for food and livelihoods. Households on the frontlines of resource use and environmental change are harbingers of the patterns of resource use, ramifications of policy, and sustainability of environments. Moreover, households reliant on natural resources are most at risk of food and income shortfalls in changing environments.

6. REFERENCES

Carter, N. H., A. Vina, et al. (2014). "Coupled human and natural systems approach to wildlife research and conservation." Ecology and Society 19(3). Coates, J., A. Swindale, et al. (2007). Household food insecurity access scale (HFIAS) for measurement of food access: indicator guide. Food and Nutrition Technical Assistance Program (FANTA). I. D. Academy for Educational Development Inc (AED) and USAID Bureau for Global Health Office of Health, and Nutrition. Washington, DC. Corvalán C, Hales S, et al. (2005). Ecosystems and Human Well-being: Health Synthesis. World Health Organization. Geneva.

! 29 Fiorella, K. J., M. D. Hickey, et al. (2014). "Fishing for food? Analyzing links between fishing livelihoods and food security around Lake Victoria, Kenya." Food Security: 1-10. Hummel, D., S. Adamo, et al. (2013). "Inter- and transdisciplinary approaches to population- environment research for sustainability aims: a review and appraisal." Population and Environment 34(4): 481-509. Kenya Ministry of Health (2013). Kenya County HIV Service Delivery Profiles. Republic of Kenya, Ministry of Health. Liu, J., T. Dietz, et al. (2007). "Complexity of coupled human and natural systems." Science 317(5844): 1513-1516. Liu, J., T. Dietz, et al. (2007). "Coupled human and natural systems." Ambio 36(8): 639-649. Liu, J. G., Z. Y. Ouyang, et al. (1999). "Changes in human population structure: Implications for biodiversity conservation." Population and Environment 21(1): 45-58. Mbita Division (2009). Population Projection. Kenya, Government of Kenya. Nagata, J., K. J. Fiorella, et al. (2013). "Socio-demographic and health associations with body mass index at the time of enrollment in HIV care in Nyanza Province, Kenya." AIDS Care 25(12): 1491-1498. Nagata, J. M., K. J. Fiorella, et al. (2014). "Around the table: Food insecurity, socio-economic status, and instrumental social support among women living in a rural Kenyan island community." Ecology of Food and Nutrition In Press. Nagata, J. M., R. O. Magerenge, et al. (2012). "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 24(6): 728-736. Ostrom, E. (2009). "A General Framework for Analyzing Sustainability of Social-Ecological Systems." Science 325(5939): 419-422. Schlueter, M., R. R. J. McAllister, et al. (2012). "NEW HORIZONS FOR MANAGING THE ENVIRONMENT: A REVIEW OF COUPLED SOCIAL-ECOLOGICAL SYSTEMS MODELING." Natural Resource Modeling 25(1): 219-272. Walker, B., C. S. Hollin, et al. (2004). "Resilience, adaptability and transformability in social- ecological systems." Ecology and Society 9(2). World Bank (2013). Agriculture and Rural Development. T. W. B. Group. Washington, DC.

! 30 Chapter 4. Effects'of'Human'Illness'on'Environmental' Sustainability

1. INTRODUCTION

Environmental and human health are widely recognized as inextricably linked (Corvalán et al. 2005; Millenium Ecosystem Assessment 2005; IPCC 2014). Landscape change and declining biodiversity have increasingly been identified as key causal factors in the spread and proliferation of infectious diseases from malaria to dengue fever. Environmental change amplifies a range of human illnesses (Patz et al. 2008; Myers et al. 2013). Yet we rarely explore the reverse pathway: the impact of human illness on environmental change and resource sustainability.

Households, communities, and nations may alter their pressure on environmental resources in several ways as a response to illness. Illness changes use of natural resources by reducing engagement in resource-dependent livelihoods and shifting use of the environment. Shifting use of the environment, the more complex of these pathways, includes both altered activities and turning to the environment as a safety-net in times of illness-induced food and income insecurity. The experience of illness itself constitutes a ‘shock’ that activates coping strategies (Kgathi et al. 2007; Baylies 2002). Whether human illness curbs or exacerbates environmental pressure is theoretically unclear (Damon et al. 2015); research indicates both increases in reliance on wild foods, meats and resources, and declines in agricultural productivity in response to illness. Ecological knowledge and stewardship may be broadly affected by a need to forestall medical bills, physical limitations, deaths, and a fatalistic perspective, or perceived loss of agency (Allison and Seeley 2004b).

Though concerns have been raised as to the impact of illness on the environment, the links from illness to lower labor participation are often assumed to also diminish environmental pressure. On a household-level, mortality and morbidity change both the physical capacity of households as well as household planning horizons. Here, we review the literature on disease and the environment, develop a framework to understand the impact of illness on the environment, and examine our framework using a case from an HIV-affected community around the Lake Victoria fisheries in Kenya.

2. LITERATURE REVIEW

Links among disease and labor have perhaps been best understood through the case of HIV in Africa. Throughout much of Africa, rural households are reliant on resource-dependent livelihoods, such as agriculture or fishing. HIV is theorized to impact resource-dependent livelihoods through combined effects of mortality, morbidity, or the debilitation associated with illness, and their effects on incomes (Bolton and Talman 2010; Oglethorpe and Gelman 2007; Talman et al. 2012; Matiru and Osur 2008; Fiorella 2013). HIV reduces physical capacity to work, increases medical expenses, shifts family outlooks and can lead to the loss of a

! 31 breadwinner –with implications for livelihoods, income, and ecological knowledge (Talman et al. 2012; Matiru and Osur 2008; Torell et al. 2006). These effects contribute to HIV-affected households experiencing more food and income insecurity than their neighbors (Gillespie and Kadiyala 2005; Anema et al. 2009; Ndirangu et al. 2013). Further, the higher levels of food insecurity and income poverty experienced by HIV-affected households, in turn, amplify disease risk and poor health outcomes (Gillespie and Kadiyala 2005).

Although HIV’s particular etiology is best documented and remains acutely relevant in our review and case study, the effect of illness on the environment can also be generally understood through this lens regardless of the disease. Resource-dependent livelihoods, poverty, and biodiversity tend to converge in communities with broad exposure to varied illnesses and limited access to healthcare. Similar dynamics likely accompany a range of illnesses. In much of the tropics, chronic infectious disease exposure and illness may drive similar dynamics, even in the absence of high HIV prevalence.

Reduced Engagement in Resource-Dependent Livelihoods

HIV mortality may decrease days worked and effort for people harvesting natural resources with a consequent reduction in intensity of environmental impact. HIV morbidity has reduced production among farmers, for example in commercial tea, homestead banana, and subsistence farming systems (Fox et al. 2004; Byrne 2002; Nguthi and Niehof 2008). The ‘new variant famine’ hypothesis builds on this evidence to posit that by eroding rural livelihoods, HIV has changed households’ food and income security coping strategies and contributed to food shortages in Southern Africa (de Waal and Whiteside 2003). The contribution of HIV to macro level food shortages has been supported by evidence of these dynamics in Zambian agriculture (Mason et al. 2010). This hypothesis suggests that mortality and morbidity reduce both labor productivity and household planning horizons.

The experience of illness as a shock may cause shifts to coping strategies, or adoption of posthoc livelihood strategies to get by (Kgathi et al. 2007; Baylies 2002). For example, a household’s size and thereby its ability to substitute labor in the face of illness affected whether coping strategies impacted soil fertility in Western Kenya (Damon et al. 2015). As strategies shift, households are likely to perceive greater challenges in carrying out their livelihoods and are more vulnerable to exogenous environmental perturbations. Further, households may experience compounding shocks as enduring effects of engaging less desirable coping strategies.

The Environment as a Safety-Net

HIV-affected households may also rely disproportionately on the environment as a safety-net, targeting wild foods, fuelwood, and other wild resources to cope with food and income shortages. These safety-net resources are available on shorter time-scales, have elements of open source accessibility, and may be less expensive to access, yet they are also often less desirable, lower yielding, or illegal. While higher-income households typically exert a higher environmental impact (Shackleton and Shackleton 2006; Wunder 2001), safety net strategies are associated with poverty. In some cases, such strategies suggest a net reduction in environmental impact, while in others the particular activities (e.g. hunting, charcoal production) and ecosystem

! 32 sensitivity may exacerbate environmental degradation. Bushmeat harvest is a safety-net strategy that notably increases environmental impact in rural areas (Brashares et al. 2011).

Several cases suggest HIV-affected households may rely disproportionately on wild plant and animal foods, including insects, reptiles, birds, and mammals (Hunter et al. 2007; McGarry and Shackleton 2009), and other natural resources, notably timber and forest products (Challe and Struik 2008; Anyonge et al. 2006; Barany et al. 2004). Yet some evidence also suggests HIV households’ reliance on animal foods may not be disproportionate (Kaschula and Shackleton 2012; Kaschula 2008).

The fishery sector, with more immediate returns on labor investment than agriculture, also features elements of a natural resource safety net. Fishing households in Botswana, Ghana, and Uganda report that HIV-related morbidity and mortality have altered or reduced their fishing activities (Ngwenya and Mosepele 2007; Tham-Agyekum et al. 2011; Tanzarn and Bishop- Sambrook 2003). Further, illness has changed livelihoods in Uganda as fishers unable to withstand the rigors of deep-water fishing have displaced female fish sellers on shore (Seeley et al. 2003). On a community-level, where resource management depends on long-term perspective and increasingly decentralized co-management systems, HIV may threaten responsible fishery management (Allison and Seeley 2004b). In particular, where HIV fells adults a less experienced younger generation may take over fishing activities before acquiring sufficient ecological knowledge (Tanzarn and Bishop-Sambrook 2003).

3. A FRAMEWORK FOR THE IMPACT OF HUMAN HEALTH ON THE ENVIRONMENT

Based on our review of the literature on illness and the environment and qualitative assessments of the relationships involved, we expound here the pathways through which human health impacts the environment (Figure 1). Our framework applies particularly to rural households, though is applicable to peri-urban and urban households with access to natural resources. The pathways depicted show the possible trajectories of a single household, with multiple pathways possible in each household. While empirical data exists to support some of these pathways, others are relatively less explored. In particular, research efforts have yet to examine how changing livelihood activities resulting from illness may impact the environment. Finally, we provide a unidirectional framework, though feedbacks certainly exist.

The aggregate effects of an individual or set of pathways are variable; relative contributions to increased or decreased environmental pressure will ultimately be shaped by factors specific to the context, household, and environment. In general, factors that reduce livelihood effort suggest a diminished environment impact. Factors that engage the environment as a safety net suggest the impact on the environment will increase. Finally, factors that alter activities may increase or decrease the environmental impact, depending on the particular circumstances. In this relatively unexplored scenario, illness may drive household adaptation to lower yield yet higher environmental impact activities as households adjust the physical effects of illness and risks of environmentally destructive, and sometimes illegal, activities.

! 33 A range of contextual factors will shape the strategies employed when a given household responds to illness and the environmental impact of those strategies. Central among these factors are the environmental resources that one engages with – fish, terrestrial wildlife, forest products or agricultural land. The resources available and features of a household will shape the activities and alternatives that household can access (Ribot and Peluso 2003). Further, resource reliance is shaped also by differences in physical demands to harvest, financial investment needed, and ecological knowledge required; factors that are often altered in households affected by illness. Finally, the adequacy of healthcare has the potential to alter the duration, severity, prognosis of illness and thereby the consequences for environmental impact.

Disease& Capital& Reduc?on&in&Capacity& Investment&! Eﬀort&Increase& Changing&Ac?vi?es& Harvest&& Eﬀort&! Environmental& Illness& Livelihood& Impact&! Ac?vi?es&Δ

Family& Environmental& Vulnerabili?es&"& Impact&"& Death& Ecological& Knowledge&!&

Figure 1: Pathways through which human disease affects the environment at a household level. Disease causes illness and, sometimes, death with consequent effects on the ways in which people engage with the environment via livelihood and safety net mechanisms. Boxes outlined in red indicate areas where illness and death in a household decrease capacities, green where effort increases or is displaced, and purple where activities change. While many of these mechanisms have a known or projected environmental impact, changing livelihood activities may increase or decrease environmental impact. It is the uncertainty created by changing livelihood activities that we aim to further explore with the following case study from Lake Victoria’s fisheries.

4. CASE STUDY: LAKE VICTORIA FISHERIES

To examine the proposed pathways that lead from human disease to environmental impact, we use evidence from the Lake Victoria fishery. Lake Victoria is emblematic of HIV-affected fisheries around the world, and offers a useful analog to consider the impact of disease on environmental sustainability.

! 34 a) Background

HIV and Fisheries

Fisheries, including those in coastal regions and inland lakes, are often the sites of high HIV prevalence, particularly in Africa and Asia (Smolak 2014; Opio et al. 2013; Gordon 2005; Allison and Seeley 2004a) with widespread HIV among fishers attributed to interactions among migration, exchanges of sex, and persistent food insecurity (Allison and Seeley 2004a; Smolak 2014). Prevalence of HIV exceeds 20% in many African fisheries, eclipsing the prevalence of the general population by over 4.5 times (Kissling et al. 2005; Nagoli et al. 2010).

In Lake Victoria, the introduction of non-native Nile perch (Lates niloticus) coincided with the rise of the HIV epidemic. Nile perch caused a crash in the lake’s biodiversity (Witte et al. 1992) as well as an export boom and influx of migrants who arrived to harvest fish throughout the 1980s and 90s (Balirwa 2007). Today, HIV prevalence in lakeshore communities exceeds 25% (Kwena 2010; Kenya Ministry of Health 2013; Asiki 2011).

Lake Victoria Fishing Methods and Environmental Impact

The methods of fishing practiced in Lake Victoria differ in their physical demands, capital requirements, targeted species and environmental impact. We explain below the current dynamics of fish catch and fishing methods to provide background on the current state of the fishery and fishers’ options. The extent to which illness may reduce engagement in fishing livelihoods or alter activities is dictated by the context in which fishers switch or scale back their efforts.

The effects of fishing methodologies on the long-term health of the Lake Victoria fisheries is of particular concern as destructive fishing practices and unchecked harvest pressure has ushered in a decline in fish catch. Current projections indicate that since 2002 Nile perch have declined by 65% in inshore areas and 30% in deep zones (Taabu-Munyaho et al. 2014), while catch-per-unit- effort declined 40% (Omwoma et al. 2014). However, a sardine-like fish, dagaa (Rastrineobola argentea), is an increasingly important fishery; as Nile perch has declined sharply, dagaa’s share of lake biomass has expanded and catch has doubled (Taabu-Munyaho et al. 2014).

Table 1 provides an overview of the most common types of fishing methods. Several of the most common fishing methods – beach seines, monofilaments, and drifting gillnets– are illegal and destructive (Table 1). A co-management system issues permits to fishers, collects catch data and regulates fishing gears and catch, with enforcement by local Beach Management Units, Ministry of Fisheries Development and bilateral lake-wide authorities. Regulations, however, are not strictly enforced (Eggert and Lokina 2009). Further, the various fishing methods require different degrees of physical effort, which may be affected by illness. One or more fishers have generally made a capital investment in the nets and/or boat, while the remaining 2-5 fishers invest labor. In some cases, a boat or net owner will contribute only materials and will not join the fishing crew.

Beach seines and gill nets have long been implicated in the depletion of inshore Lake Victoria fisheries (Merten 1979; Lake Victoria Fisheries Organization 2012; Okeyo 2014). These

! 35 methods, along with monofilament nets, capture a high proportion of juvenile fish and cause habitat destruction in shallow fish breeding areas (Tietze et al. 2011; McClanahan and Mangi 2004; Mangi and Roberts 2006). Yet, while beach seining is more profitable than gillnet fishing for fishers that make capital investments in gears, it is the least profitable fishing activity for fishers that contribute labor only (Mangi et al. 2007). Fishery role thus substantially affects relative income and catch per unit effort for each method.

A scenario where a range of destructive methods predominate fish harvest and enforcement is limited is not unique to Lake Victoria. In such a context, the factors that shape fishing method choice, however, have important the consequences for fishery sustainability.

Table 1: Primary Lake Victoria fishing methods and their environmental impact. Method Description Target Regulations Environmental Relative physical & travel Species (LVFO 2004) impact demands Monofil- Nylon gill nets Nile Illegal • Targets juvenile fish • Low physical demands ament perch • Inshore competition • No travel; On-shore Beach Long (>150m), Nile Illegal • Habitat destruction • Low physical demands seine mesh nets (average perch • High proportion of • No travel; On-shore 2”-4”); weighted juveniles caught and buoyed lines • Inshore competition used to pull into (McClanahan and shore; not selective Mangi 2004; Mangi and Roberts 2006) Gill net Vertical or drifting Nile Drifting • High proportion of • Moderate physical nets used to perch; gillnet juveniles caught demands selectively catch Tilapia (tembea) • Inshore competition • Near-shore; Limited fish in mesh slots; illegal; Min. (McClanahan and travel size selective; mesh size, Mangi 2004; Mangi and 5”; max. net Roberts 2006) number 26 Long line Mainline carrying Nile Legal; Min. • Minimal impact – • Moderate physical ganglions with perch hook size targets larger fish in demands baited hooks deeper waters • Deep water; High travel Light Night fishing Dagaa Legal; Min. • Minimal impact – • High physical demands fishing/ employing a light mesh size, targets expanding • Overnight; High travel small to attract fish and a 10mm fishery seine fine mesh net

b) Methods

Study Site

We conducted this study on Mfangano Island, located within Homa Bay County in Nyanza Province, Kenya. A continental island in Lake Victoria, Mfangano is approximately 65km2 and home to 21,000 (Mbita Division 2009). Fishery involvement, both for trade of fish and subsistence use, is widespread (Fiorella et al. 2014). Mfangano has limited health infrastructure and electricity, and no running water or paved roads. Food insecurity is common throughout Mfangano and ubiquitous among people living with HIV/AIDS (Nagata et al. 2012; Nagata et al.

! 36 2013; Nagata et al. 2014; Fiorella et al. 2014). HIV prevalence is over 25% among adults (Kenya Ministry of Health 2013).

Survey Methods

The data were collected from December 2012 – March 2013 and are a subset of a two year prospective cohort study of fishing livelihoods, fish consumption and child nutrition. Data include 4 time points: baseline, 3-months, 6-months and 12-months. Data were collected for 303 participant households randomly selected from an enumerated sampling list of all households with a child <2 years of age and living on Mfangano Island, Kenya. Data presented here are those from adult male respondents, who were initially present in 251 households (83%). Local enumerators conducted surveys in Dholuo, the local language. We obtained written consent from study participants prior to enrollment.

Surveys were developed through a compilation of validated measures and adaptations of locally relevant measures. The Measured Outcomes Survey-HIV was used to calculate morbidity scores (Revicki et al. 1998; Wu et al. 1997; Wu et al. 1991; Wu 2009), which were centered at 0 and normalized by standard deviation. Household shocks and perceptions indicators were developed based on consultation with local researchers and on-going experience in the region. Fishing activities surveys were created based on Lake Victoria frame surveys documenting fishing methods and frameworks for tabulating them (LVFO 2012). Fishers reported fishing role, region, income, experience of shocks, and fishery perceptions (e.g. factors that affected their fishing) over the preceding 3 months.

Statistical Analyses

We compared demographic factors and fishing effort across time points, fishing activities and morbidity score quintiles. We use Chi-squared tests for independence to test for associations among these variables and the Bonferroni correction to adjust levels of significance for multiple comparisons. We used univariate logistic regression models to assess the relationship between morbidity and the experience of shocks or perceptions of the fishery.

We used conditional fixed effect panel models using Stata v12.1 (StataCorp LP; Texas, USA) and maximum-likelihood estimation to estimate the likelihood of fishing with a particular method (Equation 1).

Equation 1. ! The subscript i represents the individual and t represents time point. β and are treated as parameters. The likelihood of given data is conditioned on the number of positive! outcomes for each individual and does not depend on the , so the model can use maximum likelihood !

! 37 estimation for the β parameters. In other words, the model uses maximum likelihood estimation based on differences across fishing outcomes within an individual. The condition is on the pattern of the outcomes for each individual. The model considers the outcome (yes/no on a fishing method) and set of predictor variables (morbidity score, fishing income, fishing role) at each of 4 time points. It looks at individuals that do not have the same outcome variable at every time point (i.e. households that change in and out of the fishing method) and drops individuals that do have the same outcome at every time point (i.e. always fish with this method or never fish with this method). Thus, the model estimates the within-individual differences across time points by using the individual as a control for itself in estimating the effect of the predictor variables when the outcome is present as compared to the predictor variables for the time points when the outcome is not present. The approach controls for all the time-stable characteristics (e.g. gender, ethnicity) of an individual, both measured and unmeasured. (Allison 2005; Williams 2015)

We transformed the estimated coefficients to odds ratios (eb), and similarly transformed standard errors and 95% confidence intervals. With fixed effects for time point and household, we model the effect of morbidity, fishing role (e.g. laborer, invested/laborer, owner) region, and fishing income on each fishing method (outcome variable, available at each time point). Because region did not affect odds ratio estimates, we selected parsimonious models omitting this variable. The resultant fixed effects models include all individuals that used a particular fishing method at any of the 4 time points to estimate within-individual differences.

As fishing methods were not exclusive, meaning fishers often participated in more than one type of fishing, we were unable to concurrently estimate engagement in fishing activities with a multinomial model. However, we examined correlations between fishing methods and, with the exception of two pairwise groups, all correlations were less than |0.2|. We ran multinomial models inclusive of correlated outcomes (e.g. for each individual fishing activity and correlated fishing activities) and observed that the ordering of estimation was unchanged. We present the conditional fixed effects panel models of each individual fishing activity, which provide for both higher power and the most meaningful outcome.

c) Results

Descriptive statistics of fishing methods used by all fishers (n=253) and averaged across time points are provided in Figure 2. More than half of the time fishers participated as laborers (56%), with fishers providing labor and capital investment in 29% of the time and acting only as gear owners in 15% of the time. On average, fishers spend 13.5 days fishing each month and 5.7 hours on each fishing trip.

Descriptive statistics also demonstrate limited differences in fishery role and fishing effort across morbidity scores (Table 2). Quintiles for morbidity score were created inclusive of all adults, including men and women who are fishers and non-fishers.

! 38 ! Fishing Effort

a) b)

Catch-per-Unit Effort

c) d)

Fishery Roles

e) *Beach seining may involve multiple trips over the course of a day, as compared to other activities typically completed in a single daily trip, consequently this value cannot be compared to other methods.

Figure 2: (a, b) Average fishing effort, (c, d) average catch per unit effort, and (e) fishery roles by fishing method. Participant reports of recent effort exerted and income per effort were used to calculate averages in hours (light green) and days (dark green) across fishing methods. In (a-d), bars represent average values and lines represent standard deviations. In (e), the proportion of fishers (n=253) in each role are presented.

! 39

Fishing Effort

a) b)

Catch-per-Unit Effort

c) d)

Fishery Roles

e)!

Figure 3: (a, b) Average fishing effort, (c, d) average catch per unit effort, and (e) fishery roles by morbidity score quintile. Morbidity score quintile 1 is the lowest experience of morbidity, while 5 is the highest experience of morbidity. Participant reports of recent effort exerted and income per effort were used to calculate averages in hours (light green) and days (dark green) across morbidity score quintile. In (a-d), bars represent average values and lines represent standard deviations. In (e), the proportion of fishers (n=253) in each role are presented.

! 40 Our analysis of the relationship between morbidity and fishers’ recent experience of shocks by univariate logistic regressions revealed that morbidity was associated with a range of shocks, including whether other household members had recently died or experienced illness, fishery prices, environmental dynamics, and loss of gears (Figure 3).

Further, morbidity was also associated with perceptions that various factors affected ones’ ability to fish. These results indicate that people who are sicker have a higher odds of reporting that they were affected by fishing regulations and the physical difficulty of fishing (Figure 3). That fishers perceive a range of factors affected fishing, may be a consequence of or motivation to change fishing behavior. !

! ! Dependent'Variable' ! Figure 3: Associations among morbidity score and (a) experience of shocks and (b) perceptions of factors that effect fishing at baseline. The univariate logistic regression odds ratios (circle) and 95% confidence intervals (vertical lines) associated with morbidity score are depicted for each type of shock and each perception of factors that affected your fishing in the last 3 months. The odds ratios indicate the odds of experiencing a particular shock or fishery perception with a 1- unit increase in morbidity score, normalized by standard deviation. Where the 95% confidence intervals cross 1, the association is not significant.

Fixed effects logistic regression panel models indicate the relationship between morbidity and particular types of fishing (Table 3, Figure 4). The full, longitudinal models use each type of fishing as an outcome variable and control for fishery role and income. Participation in a particular type of fishing is non-exclusive, and 25% of fishers participate in more than one type of fishing.

! 41 Table 3: Conditional fixed effects logistic regression panel models predicting participation in fishing activities. Outcome Monofilament Beach Seine Gillnet Long Line Small Seine 95% OR SE 95% CI OR SE CI OR SE 95% CI OR SE 95% CI OR SE 95% CI Morbidity Score 2.26 * 0.89 1.05-4.87 1.12 0.39 0.58-2.21 1.67 0.58 0.85-3.30 0.98 0.44 0.41-2.36 0.36 ** 0.13 0.18-0.74 Monthly Income 1.25 0.35 0.73-2.16 0.74 0.18 0.47-1.18 1.07 0.22 0.72-1.62 1.22 0.47 0.57-2.6 1.49 0.39 0.90-2.49

+ Role Owner 8.79 ** 6.75 1.95-39.60 0.65 0.43 0.18-2.35 1.21 0.57 0.48-3.03 0.40 0.39 0.06-2.69 2.04 1.53 0.47-8.84

Laborer, invested 5.21 4.81 0.85-31.80 0.46 0.41 0.08-2.66 0.86 0.61 0.21-3.47 0.63 0.69 0.07-5.38 6.26 * 5.85 1.00-39.10 Time ++ Point 3 mon. 1.12 0.65 0.36-3.49 0.52 0.26 0.20-1.36 0.80 0.32 0.48-3.03 0.94 0.71 0.22-4.09 3.63 * 1.89 1.31-10.09

6 mon. 2.54 1.55 0.71-9.12 0.59 0.31 0.21-1.66 0.75 0.32 0.33-1.72 0.36 0.30 0.07-1.80 2.85 * 1.51 1.01-8.03 + 12 mon. 3.10 2.08 0.83-11.52 0.66 0.35 0.23-1.89 0.55 0.25 0.23-1.33 0.59 0.44 0.14-2.52 1.34 0.76 0.44-4.09 *0.05, **0.01 + ++ reference category: laborer; reference category: baseline

Associations)between)Morbidity)and)) Fishing)Methods)(adjusted)models)) 5"

1" Morbidity)Odds)Ratio) 0" Monoﬁlament" Beach"seine" Gillnet" Long"line" Small"seine" Dependent)Variable))

Figure 4: Associations among morbidity score and fishing type. The conditional fixed effects logistic regression panel models odds ratios (circle) and 95% confidence intervals (vertical lines) associated with morbidity score are depicted for each fishing method. The models include covariates income, fishery role (laborer, owner, both) and time point, and account for fixed effects by participant and time point. The odds ratios indicate the odds of fishing with a particular method, arranged from lowest to highest physical difficulty, with a 1-unit increase in normalized morbidity score, holding other covariates constant. Where the 95% confidence intervals cross 1, the association is not significant.

! 42 d) Case Discussion

We find that morbidity has a strong association with particular methods that individuals use to fish. The relationship between illness and fishing methods, even when adjusted for income and fishing role suggests physical demands and outlook substantially shape how people engage with specific livelihood activities and the environmental consequences. With higher morbidity, fishers are more likely to participate in illegal and destructive fishing activities (e.g. monofilament) and less likely to participate in the most sustainable and physically demanding fishing activities (e.g. small seine).

The experience of household and fishery shocks, as well as perceptions of increased challenges in fishing further support this relationship. Fishers who experience more illness perceive the fishery to be physically more demanding. In addition, that fishers who experience more illness also perceive fishery regulations as affecting them and are more likely to have had gears confiscated may be an effect of fishing with illegal methods (monofilament, beach seine, and some types of gillnets).

The association between other types of shocks and illness belies the range of household factors that coincide with illness and decisions to alter fishing behavior. Fishers report widespread experience of recent family deaths (27% of households, over 1 year) and ubiquitous experience of family illnesses (63% of households, over 1 year). Though we focus here on the effects of illness on individuals who are fishing, there are likely substantial spillover effects of family illness and deaths on the ways that households engage with the environment. Environmental ramifications of illness may also result from changing behavior of family members, for example, widows and vulnerable women on Mfangano often partake in beach seining despite receiving a fraction of the pay of men.

Associations between morbidity and certain fishing practices suggest illness may increase inshore fishing competition, cause habitat destruction, increase targeting of juvenile fish, concentrate fishing pressure in an overexploited fishery, and drive people to use illegal methods. With higher levels of morbidity, the odds of participating in environmentally destructive, illegal monofilament fishing, though not statistically significant, are more than 2.26 times greater (Adjusted odds ratio: 1.57, 95% Confidence interval: 0.88-2.79). Conversely, with higher levels of morbidity, odds of fishing with small seines for dagaa, presently the most sustainable Lake Victoria fishery, are about one third. Because of the inverse relationship between fishing method sustainability and effort required, morbidity’s influence on fishing method choice also impacts fishery sustainability.

The methods chosen (monofilament) and avoided (small seine) when people are ill concentrate fishing effort on or near shore, where Nile perch have declined by 65% since 2002 (Taabu- Munyaho et al. 2014). Although not statistically significant, odds of using beach seines and gillnets, on and near shore methods, and long line, a deep water method, with increases in morbidity are also suggestive of this pattern. Further, these methods target juvenile Nile perch, affecting the fishery age structure and concentrating fishing effort in a heavily exploited fishery. In contrast, dagaa biomass is expanding (Taabu-Munyaho et al. 2014). Fished with small seines

! 43 in deep waters, this methodology is eschewed with increasing illness. Around Lake Victoria, the associations between illness and various fishing methods suggest a direct effect of human illness on the long-term sustainability of the Lake Victoria fishery.

While we often assume that illnesses that harm people dependent on natural resources will decrease pressure on those resources due to decreases in effort, we find little evidence of differences in fishing effort related to illness. In fact, individuals with low levels of illness are less likely to be fishing, suggesting they are engaged in other livelihood activities, including professional and non-subsistence employment. Similar conclusions about the unlikeliness of fisher deaths to reduce fishing pressure have been reached in research considering the impact of HIV on fisheries across Africa (Allison and Seeley 2004b). Yet, the effect of illness on resources may still be substantial where illness drives changes in the ways people engage with the environment.

Almost by definition, the fishing methods that are least discriminating in their harvest and most deleterious to the environment are most likely to be chosen when a fisher has less physical effort to put forth. The willingness to partake in fishing methods prohibited by regulations may also be a function of the outlook of chronically ill fishers. Especially in the case of lethal diseases or chronic experience of illnesses, the poor health of individuals may substantially shape the degree to which they are able to plan for or attend to environmental sustainability.

5. DISCUSSION & CONCLUSION

We often assumed that illness and death reduce environmental pressure, and reduction in labor capacity has long been observed in agricultural systems. Yet evidence from Lake Victoria suggests that salient pathways through which human illness shapes livelihood decisions and environmental pressure may be starkly overlooked.

The role of illness in affecting livelihood strategies and thereby environmental sustainability has been largely underappreciated and unexplored. Illness may cause harvesters to shift their priorities in assessing catch-per-unit-effort opportunities and to eschew methods that require high physical effort while shifting outlooks on the environmental consequences of the methods chosen. This finding has potentially broad applicability to other systems and underscores the importance of better understanding the cyclical ways through which human health and the environment shape each other.

While our work was conducted in an HIV-affected community and much of the literature on these dynamics focuses on HIV, the experience of frequent illness is not unique to individuals living with HIV/AIDS. The social and economic consequences of a range of illnesses such as malaria and tuberculosis are substantial in many parts of the world, and especially in Africa (Sachs and Malaney 2002; Kim et al.). A study of morbidity in Kenyan adults found that over 2 years, staggeringly, men were ill 19% of days and women were ill 41% of days (Murray et al. 1992).

! 44 The extent of time in which people are sick and individuals’ perceptions of their prognosis undoubtedly shapes their livelihood engagement, outlook, and the sustainability of practices. The time horizons of resource harvest also likely play an important role. Our work in a fishery system, where yields are realized immediately, contrasts with that in agricultural systems where planting proceeds harvest by months and regular inputs of time and effort are needed throughout. Resource harvests that quickly yield benefits – fishing, hunting, harvesting forest products, burning charcoal – might thus be treated differently in times of illness. The impact of these resource extractions may be significant, and may be amplified by lost ecological knowledge or the needs of surviving families who turn to the environment as a safety net. Further, the environmental degradation begotten from overharvest or destructive practices may drive the cyclical effects that lead from environmental destruction to poor health outcomes.

Our research suggests that the health of our natural resources is entangled in the health of the people that rely on them. Thus, meaningfully addressing the needs and health of people who rely on natural resources may be instrumental in ensuring environmental sustainability. Meeting basic needs for healthcare and medications may also shape the physical effort and long-term perspective that people are able to bring to their livelihoods and the pressure they exert on the environment. Where enforcement of environmental regulations remains a key challenge for protected areas, forests, fisheries and other resources (Murray et al. 1999; Bruner et al. 2001), providing for the health of human populations may play a role in curtailing destructive practices.

The pathways we posit (Figure 1) merit further consideration and research to understand the circumstances in which they operate to shape environmental impact and long term study to appreciate the causal dynamics at play. Nowhere is this more important than in the ecosystems where people experience a high burden of illness and rely on natural resources to meet basic needs. Deepening our understanding of the ways that human illness impacts the environment is critical to appreciating the ways that illness constrains resource management and to addressing the linked fates of human and environmental health.

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! 50 Chapter 5. Transactional Fish-for-Sex Relationships Amid Declining Fish Access in Kenya

This chapter is in press for publication and is reproduced here with kind permission of the co- authors and Elsevier.

Fiorella, K.J., Camlin, C., Salmen, C.R., Omondi, R. Hickey, M.D., Omollo, D.O., Milner, E.M., Bukusi, E.A., Fernald, L.H., Brashares, J.S. 2015. Transactional Fish-for-Sex Relationships Amid Declining Fish Access in Kenya. World Development. (In press)

ABSTRACT

Women’s access to natural resources for food and livelihoods is shaped by resource availability, income, and the gender dynamics that mediate their access. In fisheries, where men often fish but women comprise 90% of traders, transactional sex is among the strategies used by women to access resources. Using the case of Lake Victoria, we employed mixed methods (in-depth interviews, n=30; cross-sectional survey, n=303) to analyze the influence of fish declines on fish- for-sex relationships. We found that fish declines affect relationship duration and women’s bargaining power. Our results have broad implications for the dynamics of economies dependent on increasingly scarce resources throughout the world.

1. INTRODUCTION

Populations reliant on natural resources for their food and livelihoods are particularly vulnerable to environmental change and resource extraction (Brashares et al. 2014; IPCC 2014). For harvesters of fish, crops, and forest products, the natural resources they depend on serve not only as a source of livelihoods, but also a dietary safety net during times of hardship (WRI 2013; FAO 2014). Efforts to maintain access to critical and declining natural resources may involve many forms of violent conflict and social injustice (Brashares et al. 2014). Recent research has highlighted a pervasive but less studied strategy for accessing natural resources, the exchange of sex for goods. Transactional sex has been reported as a strategy to access a range of natural resources, including forest products, fuelwood, food and water (Malawi Government 2007; Samuels et al. 2008; UNHCR 2011). In their groundbreaking paper, Béné & Merten (2008) highlight the role of transactional sexual relationships as a means of gaining access to a globally significant and declining natural resource: fish.

An estimated 10-12% of the world’s population relies on fisheries to meet their food and income needs (FAO 2014). Yet, nearly all global fish stocks are fully or overexploited (FAO 2014). Losing access to fish resources results in a range of negative social and development consequences, including exploitative labor practices, food and nutrition insecurity, and environmentally destructive fishing practices (FishWise 2014; Belton and Thilsted 2014; Cinner et al. 2011). These consequences of fish decline extend also to fish traders and processors, 90% of whom are women (FAO 2014). The study of fish-for-sex relationships has illuminated their

! 51 consequences for HIV transmission (e.g., Merten and Haller 2007; Camlin et al. 2013; MacPherson 2012). We extend the existing literature on these relationships to focus specifically on the ways fish availability affects female fish traders’ power to negotiate access to fish, both in the business and sexual aspects of their relationships.

Harvested natural resources, like fish, are uniquely subject to overharvest, shortfalls, and declines. Changes in resource availability affect global prices, trade dynamics, and, ultimately, who has access to resources and at what cost. We analyze fishery resources and the effects of their decline on women’s bargaining power. Our work also offers a broader analog for the ways environmental change affecting other resources may shift power dynamics in gendered economies.

Using the case of Lake Victoria, where harvest pressures to export Nile perch to international markets has precipitated dramatic fishery decline (Omwoma et al. 2014; Johnson 2010), we analyze the ramifications of fish decline on a local scale, in the communities where fish are harvested. We employ a mixed methods approach that pairs a survey of 303 households with 30 in-depth interviews with men and women who participate in fish-for-sex exchanges. The transactional sexual relationships themselves and partners within them are locally called jaboya. We characterize the prevalence and factors associated with fish-for-sex exchanges, and situate these findings within community experiences of jaboya participation and altered relationship dynamics in the face of changing fish catch. We discuss the consequences of declining fish catch for negotiation in both the resource access and sexual aspects of the relationship. Our analysis illuminates both the ways declining resources can influence relationships on the lakeshore, and the implications of natural resource decline for human well being.

2. BACKGROUND

Lake Victoria fisheries and gender

In the 1960s, British colonial authorities introduced non-native Nile perch into Lake Victoria to commercialize the fishery (Pringle 2005b). By the 1980s, the fishery entered a period of rapid growth with the catch of Nile perch a key factor in driving migration to the lakeshores, infrastructure development, and a burgeoning international export market (Balirwa 2007; Johnson 2010). Ecologically, Nile perch overwhelmed the area’s tremendous biodiversity and caused the demise of over 300 cichlid species (Witte et al. 1992).

Socially, the influx of migrants and money quickly transformed the fishery, and, in particular, the roles of women. Where women traditionally traded and processed fish, male traders and fish packing plants increasingly dominated the Nile perch fishery, which grew into a booming export market sending Nile perch to the Middle East and Europe (Medard and Wilson 1996; Geheb et al. 2008; Johnson 2010). However, economic conditions for the people of Nyanza Province, who continue to experience the highest poverty rates in Kenya, have only improved slowly (Kenya National Bureau of Statistics 2010). Today, the Lake Victoria fishery remains strikingly gendered, with women largely excluded from fishing and trading within the main Nile perch economy (Mojola 2011; Lwenya and Yongo 2012), with consequences for local fish

! 52 consumption (Fiorella et al. 2014).

As the Nile perch population expanded underwater, the region experienced a rapid influx of migrant fisherman from across Africa and a shift to a more extractive fishing methods (Pringle 2005a). As part-time fishers invested in new fishing technology, many shifted to full-time fishing to make the investment worthwhile. Fishing strategies newly deployed on Lake Victoria included beach seines and “drifting” gill-nets (known as tembea in Swahili), each deleterious to local fish stocks. Today, Kenya’s Lake Victoria fisheries are co-managed by local beach management units and the Ministry of Fisheries Development and accessed with a license and small fee.

Recently, the Nile perch catch has declined amidst high fishing pressure and related environmental concerns (LVFO 2012). From 1995 to 2009, Nile perch catch in the highly productive Winam Gulf of Lake Victoria declined by 23% while catch-per-unit-effort declined 40% (Omwoma et al. 2014). In the wake of a declining Nile perch fishery, a small, sardine-like fish has risen in prominence. Dagaa in Kiswahili, or omena in Dholuo, the local language, is best fished at night, targeted for local and regional sale, and sold within a more informal system that remains somewhat separate from the larger Nile perch economy. Where women are often excluded from the trade of exportable Nile perch, they maintain a role in drying dagaa for sale and in the regional trade of tilapia and Nile perch too small or otherwise unfit for sale to fish packing plants. Female traders travel between beaches and trading centers across the region to procure, process, transport and sell these fish in markets for local consumption (Camlin et al. 2013).

Transactional sex

One of many types of ‘transactional sex’, exchanges of sex-for-fish are a phenomenon that has been described worldwide, with reports from economically developed and undeveloped countries (Dunkle et al. 2010; Béné and Merten 2008). Though transactional sex involves the exchange of goods or money, these relationships provide more than instrumental support. Often with a semi- regular partner, these relationships many involve the provision of care, such as food or housing, emotional support or be intertwined with courtship (Poulin 2007; Hunter 2002). This is the case for many jaboya relationships. Relationships involving exchanges of sex have been described as “one of many ties of unequal exchange” in a context of complex social interdependences and traditions of patron-client relationships (Swidler and Watkins 2007). A rich literature on transactional sexual economies in sub-Saharan Africa complicates our understanding of these relationships (e.g Hunter, 2002; Poulin, 2007; Swidler & Watkins, 2007).

In jaboya relationships, fish traders exchange sex with fishermen to gain preferential fish access. Also termed fishwives, fish mongers, and jakambi (or “customers” in Dholuo), women fish traders have long played a role in procuring, processing, transporting and selling fish (Camlin et al. 2013). Jaboya also existed for generations on Lake Victoria in the context of the polygamous marriages of traveling cichlid fisherman, but in the context of the Nile perch economy has shifted from a relational “anchor” into increasingly short-term transactional exchanges (Salmen 2009). Interestingly, the Swahili word tembea (to drift or wander) locally refers to extramarital sexual relationships, semiotically linking the emergence of drifting tembea Nile perch nets on the lake

! 53 to the emergence of drifting Nile perch fisherman on shore (Salmen 2009). Today, jaboya relationships continue to be entwined with the gendered Lake Victoria fisheries (Mojola 2011).

Transactional relationships in which people exchange fish-for-sex have been observed across the African and Asian continents, in inland and marine systems (Béné and Merten 2008; Merten and Haller 2007; MacPherson et al. 2012). In sub-Saharan Africa, fish-for-sex has garnered particular attention largely because of exceptionally high prevalence of HIV around inland lakes, including Lake Victoria (Béné and Merten 2008; MacPherson et al. 2012; Kwena et al. 2013). A burgeoning literature seeks to link HIV to environmental change (Hunter et al. 2011; Talman et al. 2012; Fiorella 2013; Mojola 2011).

Jaboya and HIV

The growth of the Nile perch fishery in the 1980s and 1990s paralleled the emergence of the HIV/AIDS epidemic (Salmen 2009). Today, the prevalence of HIV on the lake’s shores is the highest in the region at 27% among adults (Kenya Ministry of Health 2013; UNAIDS 2012). Suggested causes include food insecurity, a culture of risk among fishers, prostitution, and fish- for-sex exchanges. HIV/AIDS in fishing communities has a breadth of enduring effects on fisher livelihoods, fishing communities, and the fisheries themselves (Allison and Seeley 2004a, 2004b). Further, both male and female migration to and around Lake Victoria has compounded fishery gender dynamics, exchanges of sex, and HIV risk (Camlin et al. 2013; Camlin et al. 2014).

Jaboya relationships wherein men and women risk exposure to HIV are complex and diverse. Though prevailing narratives have posited women as victims, entrepreneurial, or in search of small luxuries, recent research shows that men or women may initiate these relationships, and women may compete for relationships with fishermen (Béné and Merten 2008; Camlin et al. 2013). Further, the value of jaboya relationships are compounded by a “gendered economy” that constrains women’s job options, compensation, and power. Exchanges of sex are a livelihood strategy in response to gendered labor markets and opportunities as well as health shocks (Mojola 2011; Robinson and Yeh 2011).

The interaction of the Lake Victoria fishery with the social dynamics of the people on the lake’s shores means that neither sexual relationships nor resultant HIV transmission can be fully understood in isolation. Fishery health, dynamism and political ecology (how social and political factors interact with the environment) also matter. Jaboya relates not only to poverty, sex, and disease transmission on the lakeshore. Rather, these relationships extend to the depths of Lake Victoria and the array of ecological factors that influence fish catch and embed jaboya within complex, globalized social and ecological dynamics.

We explore here the ways Lake Victoria ecology influences jaboya relationships. Using mixed quantitative and qualitative methods, we analyze the ways these relationships are intertwined with the fishery, and, in particular, how declines in fish catch affect both women’s power to negotiate resource access and their sexual relationships.

! 54 3. METHODS

In this study, we paired qualitative and quantitative research methods in data collection from June 2012 to August 2013. Quantitative data on prevalence of and associations with fish-for-sex informed in-depth interview on perceptions and experiences of jaboya relationships.

The quantitative data used in this study are a subset of a larger study of fishing livelihoods, fish consumption, and childhood nutrition. The quantitative data are comprised of cross-sectional survey data for 303 participant households randomly selected from an enumerated sampling list of all households with a child <2 years of age and living in a pre-defined region with a population of ~21,000 (Mbita Division 2009). In households headed by a male and female, both heads of household consented to participate in the survey; in female-headed households, only females provided consent (17% of households had only a female head of household). Men and women were interviewed separately and in private by local enumerators who conducted surveys in Dholuo, the local language. Household recruitment was facilitated by a community-based organization with strong community ties and households were offered a small token of appreciation for their participation; all households approached to join the study chose to participate.

When asked about participation in exchanges of sex, men were asked whether “you” had given food, money, job or accommodations “in exchange for sex or a sexual relationship.” Female heads of household were asked whether “anyone in your household, including you,” had received food, money, job or accommodations “in exchange for sex or a sexual relationship.” The responses to this question were also categorized to include any type of exchange as disentangling the mode of exchange for fish – at once money, a job, and food – proved impossible. The phrasing of this question provided a cover for women to disclose participation in sexual exchanges despite facing higher stigma than men, and to gathered data about female youth. While the commercial sex trade is relatively rare in the study region, it is possible that these questions also capture commercial sex relationships.

Chi-square tests are used to compare the relationship among participant characteristics for those households where sexual exchanges are and are not reported. Chi-square tests thus compare households where men do and do not report sexual exchanges, and where women do and do not report they or someone in their household participated in sexual exchanges. Where small numbers violate the chi-square assumptions, Fisher’s exact tests are used, including for categorized maternal age, household size, maternal education, food insecurity, and monthly income. Quantitative data were used to guide the development of interview guides and target participants for qualitative interviews.

Qualitative data included six months of participant observation and field notes, and in-depth semi-structured interviews with 14 men and 16 women. Interview participants were nested in the quantitative household surveys, and were randomly selected to participate based on reports that they or someone in their household participates in exchanges of sex. Additional interview participants were selected to represent variation in livelihood activities. Interviews were conducted in English and Dholuo by an American co-investigator and Kenyan research assistant and translator.

! 55 We also conducted observations of daily dynamics at 13 of the region’s 19 fish landing sites with co-managed Beach Management Units. We selected a range of small, medium, and large beaches to visit and analyzed field notes in conjunction with interview data. In some instances, the triangulation of field notes and interviews revealed inconsistencies (i.e., the under-report of stigmatized behaviors such as fish-for-sex exchanges) that were resolved through informal follow-up conversations.

Interview translations and notes were analyzed with ATLAS.ti 7 (Cincom Systems, Berlin, 2002–2014). We used grounded theory methods to generate codes and code data (Strauss and Corbin 1998). We double coded 25% of the sample to assure validity of code application.

4. RESULTS a) Quantitative findings

Results of a cross-sectional household survey conducted with 303 households (303 women, 253 men) show that 34% of men (85 men) reported they gave food, money, a job or accommodations in exchange for sex, and 10% of women (31 households) reported they or another household member gave sex in exchange for food, money, a job, or accommodations (Table 1). Men most often reported providing food (23%) and money (25%). Women most often reported they or another household member received food (5%) and money (8%). Of those who reported exchanging sex, 52% of women and 56% of men reported multiple categories (e.g. food, money, accommodation, job) of exchanges (Table 2).

Table 1: Participation in Sexual Exchanges. Any Food Money Job Accommodation Female household member gave sex for 31 10% 16 5% 23 8% 9 3% 7 2% [Item] (women report, n=303), n (%) Male gave [Item] for sex 85 34% 57 23% 62 25% 13 5% 19 8% (men self report, n=253), n (%)

Table 2: Multiple Exchanges. Count of categories of items exchanged, including food, money, job, and accommodation among people who exchanged sex.

1 Exchange 2+ Exchanges 3+ Exchanges Female household member gave sex for [Item] 31 100% 16 52% 8 26% (women report, n=303), n (%) Male gave [Item] for sex 85 100% 48 56% 12 14% (men self report, n=253), n (%)

! 56 Most men and women who exchange sex are in marital or domestic partnerships (95% of men, 74% of women) with sexual exchanges being predominantly extra-couple partnerships. Men who exchanged sex (34%) were more likely to fish for dagaa and to have a partner with lower educational status, compared to men who did not exchange sex (66%). Women who exchanged sex (10%) were more likely to have lower educational status, be unmarried or not in a relationship, and have more severe food insecurity, compared to women who did not exchange sex (90%). Further, households where women exchanged sex more often had a fisher (Table 3).

Table 3: Characteristics of all households, and households reporting sexual exchanges; Chi- squared tests compare relationships between characteristics for those that did exchange sex (characteristics listed in the table), to those who did not exchange sex. Fisher’s exact tests are used where small numbers violate chi-square assumptions. The statistical comparisons are made among 84 men and 31 women who did exchange sex to 169 men and 272 women, respectively, who did not exchange sex.

All Households with Households with Households men who women who Characteristic exchanged sex exchanged sex (n=84) (n=31) (n=303) Maternal age, mean (SD) 28.1 8.4 26.8 7.5 26.9 7.2 Household size, mean (SD) 5.7 1.9 5.5 1.8 5.2 1.8 Married / In a relationship, n (%) 267 88% 80 95% 23 74% * Maternal education, n (%) None/Some Primary 156 51% 50 60% 21 78% Primary 92 31% 21 25% 4 15% Some Secondary + 55 18% 13 15% 2 7% Food insecurity (Max. 36), mean (SD) 18.3 5.1 17.9 4.3 20.4 4.6 * Asset index 1.9 1.2 2.0 1.2 1.6 1.0 Monthly income (USD), mean (SD) $109 $107 $126 $151 * $106 $103 Income from: Fisher 114 38% 36 43% 18 58% * Farmer 52 17% 14 17% 2 6% Small business 158 52% 45 54% 16 52% Charcoal 11 4% 2 2% 1 3% Teacher 20 7% 4 5% 0 0% Target Species Fished: Dagaa 58 23% 26 31% * 5 24% Tilapia 31 13% 11 13% 2 10% Nile perch 146 59% 52 62% 15 72% * 0.05

We contextualize our quantitative prevalence of and associations with sexual exchanges in our qualitative findings to elucidate the ecological and economic factors that affect participation and negotiations in jaboya relationships.

! 57 b) Qualitative findings

We examine below the ways fish access influences relationships in the jaboya economy, the role of changing fish stocks in the short and long-term, and the balance of risks faced by participants in the jaboya economy.

Characteristics of study participants

Our sample of 30 individuals included 14 men and 16 women. Twenty four participants were primarily engaged in the beach-based fish trade, representing Nile perch fishers, dagaa fishers, boat owners, hired fishers, and Nile perch traders for large and small size fish, and dagaa processors and traders. The remaining 6 were engaged in other forms of informal sector work in the beach vicinity, former fishers or fish traders, and spouses of fishers. Participants were based at or regularly visited 18 different beaches in and around the study region. Eleven participants discussed their current or past participation in the jaboya economy. The age range of the participants was 18 – 53 years with an average age of 31 for men and 27 for women. (Appendix)

Fish access

The introduction of the invasive Nile perch precipitated the growth of an international trade where, above a certain size, Nile perch are subject to set prices by fishery managers and international traders. Participants describe access to Nile perch as a simple monetary process; a male boat owner states, “With mbuta [large Nile perch] there are prices that are regularly fixed.” He adds that for women who are largely excluded from this economy the jaboya system has arisen around the types of fish where “[…] actually you can bargain.”

In contrast to the fixed prices of the Nile perch fishery, women access the fish in ancillary fisheries: dagaa, undersized Nile perch, and “rejects”, or Nile perch not accepted by fish packers. The less profitable fish that women trade in are sold locally and regionally. Participants describe jaboya relationships as an oft requisite extra-monetary strategy to access fish in this economy. Both men and women repeatedly referenced money as insufficient to access fish for sale or food: though money is availed, a sexual relationship with a fisherman is often necessary to be allowed to make the purchase. Without a jaboya, a female beach dweller says, “You have money, but you can’t get [fish]. You can’t.” A male fisher and landlord concurs, “If you have your jaboya, you may be sure of getting [fish], but if you don’t have [a jaboya] you may have your money but miss to get food.”

Some participants also indicate the structure of the fishery payments plays a role in jaboya relationships. Boat owners reap the biggest monetary rewards of fish sales. Hired fishers, who may hold jaboya relationships, are paid a substantially smaller percentage but given the opportunity to allocate fish. Thus, the disjoint between monetary benefits (largely borne by boat owners) and sexual benefits (available to hired fishers) of fish access may also foster jaboya’s entrenchment in the fisheries. Though the monetary benefits to laborers are relatively small, they are positioned to negotiate extra-monetary benefits by allocating fish, such as sex with traders. A male fisher describes the system from his perspective as a boat owner:

! 58 When they [the fishers] are selling, you’re [the owner] supervising. You want to see your fish is being sold. To whom it is being sold is none of your business.

Marital relationships and other familial ties may also avail fish for women. The same fisher goes on to say, “I can sometimes plead with them if my relative comes.” Thus, privileged access to fish through jaboya relationships may only be necessary when other relationships do not provide enough fish or one does not hold other types of relationships with fishers. Further, jaboya relationships are most common in particular aspects of the fishing economy, from which many of our interview participants were drawn. Our quantitative findings that those who exchange sex more likely fish for dagaa bears this out.

That jaboya relationships are used for fish access entrenches these relationships within both ecological and social aspects of the fishery. Further, this portends the way changes in fish availability affect jaboya relationships.

Influences of changing fish stocks

Changes in the fisheries’ ecology that influence fish catch, species available, and fish sizes emerge as elements that also motivate, moderate, and transform jaboya relationships. Participants widely agreed that fish availability had declined in recent decades and thereby elevated the importance of jaboya relationships in accessing fish. A male dagaa fisher shares that when fish catch is low, “there is that scramble for the fish and this is now when jaboya is very necessary.” As described below, participants elucidated consequences of variability in both long and short-term fish availability. While long-term fish declines often weakened jaboya relationships and pushed people out of the fishery, acutely limited fish availability was also among the range of factors motivating entry into jaboya relationships. Acute declines or increases in fish availability also played out within jaboya relationships – increasing or decreasing partners’ reliance on each other, and sometimes driving one or both partners out of the fishery and their relationship.

Example pathways linking fish availability to jaboya relationships are depicted visually in Figure 1. This diagram draws from the qualitative data presented below to provide a schematic of possible pathways linking fish availability to jaboya relationships.

! 59

Figure 1: Illustrative depiction of pathways that may link fish catch to both short term and long term changes in jaboya relationships.

Long-term fish declines

In conjunction with declines in Nile perch fish catch, participants described declining profitability and opportunities associated with fishing. Participants frequently described the current “scramble”. The “scramble” depicted both fishers’ efforts to succeed in capturing fish and women’s to secure a sufficient quantity for sale or consumption. A male boat owner says,

There could be a lot of demand for fish, and the supply is less, so in the process of the scramble women want to please these people so they get this thing [fish]. She may have the money and just need [a jaboya] for this process of scrambling.

Most often, the “scramble” referenced fish available to local markets – undersized or reject Nile perch and dagaa. In these markets competition to access fish and the struggle to meet financial needs is most acute and directly elevates jaboya’s importance in navigating constrained access. Importantly, fish prices are not sufficiently responsive to demand; when too many women have funds to purchase fish, jaboya relationships, not prices, serve to distinguish the “success” of fish traders at procuring fish. This also reinforces quantitative findings that income and assets are not related to women’s participation in sexual exchanges.

In the context of dwindling stocks, relationships become increasingly short-lived. A male jaboya participant describes his experience of how declining fish catch affects jaboya relationships:

When we go back to the 90s […] the catch of fish was good and you find that the [women]

! 60 could get all that they wanted due to enough catch […] But the time we are in today, the catch, or the population of fish in the lake, has gone down. Very much! It has really gone down. So you find that maybe your jaboya can go and come without fish. The following day, the same thing will happen. If it happens maybe three consecutive days […] she may start to look like someone who is wasting her time and switch to another person.

Declines in fish availability strengthen the ties that bind the social and ecological systems of the lake. In the current context, even short disruptions in fish availability can affect partner choice and relationship strength, including the longevity of partnerships or the degree of reliance within them. Access to the fishery is of particular import in buffering against uncertain resource availability. In addition to raising the importance of a secure fish supply via jaboya relationships for those that remain in the fishery, declining fish availability also motivates exits from the fishery for both men and women. In many instances, participants linked declines in fish availability to local declines in jaboya relationships as people switched livelihoods (i.e. to agriculture, burning charcoal, small businesses), fewer migrants arrived, and more people migrated out. A male Nile perch trader encapsulated this common dynamic saying, “If the price is low [fishers] cannot stay there […] the females also cannot stay once the jaboyas are running away.”

Short-term fish availability

Male and female partners reported that fish availability rippled through their relationships. Changes in catch and price cycle together to affect who accesses fish, the benefits derived from relationships, and the relationships’ necessity. Short-term fish availability refers to time spans as little as a few days or up to several weeks. In the short-term, acute fish declines may motivate or reinforce jaboya relationships with traders and fishers each facing increased vulnerability.

When the short-term Nile perch or dagaa catch is low and prices rise, access to fish is restricted and jaboya may resolve or temper limits on fish access. In this way, declines in available fish affect the social system, with particular ramifications for jaboya relationships that link users to fish resources. Several people describe their entry into jaboya relationships as, among other things, at a time of acute shortfalls in fish availability. A female fish trader describes this as follows:

When the fish catch goes down many people will be in need of fish, so this one usually gives the fisherman [an] advantage. Maybe he has been looking for a lady for quite some time, so he takes advantage when the fish goes down and that lady cannot get fish from anybody apart from him.

For those already participating in jaboya relationships, declines in fish availability were repeatedly linked to the power dynamics of these relationships. A female jaboya participant describes her experience in the face of Nile perch declines:

It is the issue of decline in fish catch that has really created all these messes. Long time ago I could go and make money at the beach so I really could depend on myself and it was really not really a bother that I needed someone to stand for me in order to get fish, because fish

! 61 was so many. Today people are scrambling for fish. So I can even go as low as accepting 50KES [$0.60] from someone, or as little as just fish-for-food to go to bed with someone.

Vulnerability in the face of fish declines, however, was not confined to women. In some cases, female jaboya partners who paid for gears or provided funds in times of low fish catch supported male hired laborers. The men described periods of low fish catch compelling them to accept the woman’s price for fish. A male hired laborer says that “The issue of price brings conflict […] she will find her way, maybe by talking to mother [the boat captain], so the price will remain the same or be lowered.”

Momentary rises in fish availability also altered power dynamics in jaboya relationships. When fish catch is high, participants describe sharp increases in women’s power over how they access fish. A female dagaa trader states that when fish catch is high “I see him less […] because I can get what I want with my money.” A male boat owner says, “when the supply becomes high, actually you will be pleading with these women, these buyers. So they dictate the terms; they can do without jaboya.”

At the same time, women may target fishermen anew or within an existing relationship when a fisher is flush with money in times of plentiful fish. A male jaboya participant states that, “if I get […] more fish it means I’ll be getting more money […] that’s when the relationship increases, it strengthens. Because she’ll be looking me, seeing [… I am] now getting money and [I] may be giving her support in very many ways.”

Balancing risks

The gendered fishery economy, declining fish availability, and the coupling of these with jaboya relationship dynamics makes fisherfolk vulnerable to risks of food, income, and livelihood insecurity. Our quantitative findings similarly suggests this through a relationship between women’s participation in sexual exchanges and food insecurity. Participants weigh these insecurities against a paucity of other options and another widely recognized risk: HIV infection. For both men and women, the current context of fish availability may directly motivate a sexual exchange, despite the risks.

While references to the fishery often accompanied descriptions of increases in jaboya as competition for fish rises, narratives of declining jaboya were usually paired with descriptions of fear of HIV infection. A female dagaa trader reflects this link saying “The issue of jaboya is decreasing because many people nowadays know that issue of HIV.” The commonality of participants’ focus on a single risk – of either limited fish access or HIV infection – connoted an individual’s ability to mitigate only one of these risks. For both men and women, limited fish availability may tip the scales in motivating a sexual exchange, despite acknowledged risks. In describing this tradeoff, a female fish trader states (note: women often assist in pulling in beach seines, in these instances they are not considered the fishers but helpers and given a tiny fraction of the income relative to what fishers receive):

When you pull the net and nothing comes out of it, you get nothing. You get discouraged because you will have nothing to take home […] Sometimes you have no other ways or you

! 62 have no option. Somebody may be sick [and] you don’t know his or her status but then you have to engage in [a] sexual relationship. Sometimes you don’t even mind using the protection because it is the decision of the owner of the money maybe to use condoms or not.

In addition to motivating jaboya relationships, declines in fish availability may also drive HIV risk factors including migration, changing partners and multiple partnerships. A male former fisher says, “If you are a trader you don’t stick to one beach because you want more fish [... but] nowadays there’s a bad disease.” Despite augmenting the risk of contracting HIV, jaboya was often described as a safety net providing entry into the fishery economy for those with few resources. Widows, often HIV-affected, were regularly depicted as the female jaboya partners and male participants often described their roles as providers of both fish and a business opportunity. The scope of HIV within this heavily affected community may also affect jaboya relationships on more complex levels, as understood in the experience of a migratory female fish trader and jaboya participant:

I’m a widow; I buried my husband. I’m not thinking of getting married again so I better stay in [a jaboya] relationship […] Through my experience I am scared. I lost my parents […] my sister died, plus her husband, so they left an orphan that I’m taking care of. I have a burden and it is not really going to be a comfort to marry.

Within the globalized, declining Lake Victoria fishery, decisions about risks to health and well- being are made in a challenging context. Participants describe balancing complex risks that are not easily evaluated or mitigated, be they concern about losing another spouse or securing reliable access to an increasingly ephemeral resource. Importantly, participants describe the jaboya sexual economy both as a threat to wellbeing, health, and resource control, but also as an option, in a context in which there are few.

5. DISCUSSION

The natural resources that are involved in transactional sex shape these exchanges: jaboya relationships are embedded in environmental dynamics that affect fish availability and women’s bargaining power. The economic structure of the Nile perch fishery and changing fish stocks interact to influence the initiation, gendered power dynamics, and strength of jaboya relationships. The jaboya sexual economy is linked to the ecosystem changes that positioned Nile perch atop the food chain and economy, and, today, is entangled with current declines in fish stocks.

We find that transactional sexual exchanges in a Lake Victoria island community are remarkably common, with 34% of men reporting they exchanged items for sex, and 10% of women reporting they or another household member exchanged sex. This finding relates to research showing that in a nearby urban area transactional exchanges are normative, occurring in three quarters of nonmarital, noncommercial partnerships (Luke 2006). As reported previously, jaboya and fish- for-sex relationships in similar settings are stigmatized, with HIV prevention messages and blame frequently levied on the jaboya economy (Camlin et al. 2013; Merten and Haller 2007). The relative commonality of these relationships, despite potential under-reporting due to the

! 63 social desirability bias of self-reports of stigmatized behaviors, reinforces qualitative findings that negotiating fish access is a primary function of jaboya relationships. That the qualitative findings appear to suggest these relationships are more common than quantitative findings is likely due to selection bias in interview participants to include households with a young child. Consequently, no single men and few single women were surveyed.

Our study demonstrates the salience of ecological and economic factors for understanding a sexual economy as a range of fishery features and their management, including fish availability, access, price, species, sizes, and catch, influence jaboya relationships. We extend the work of other studies that describe the effects on jaboya of exogenous environmental factors, such as well documented algal blooms, water hyacinth, or pollution (Mojola 2011) to consider the centrality of the fisheries’ ecology for these relationships.

Within a household, however, it is often a struggle over cash, to which men have privileged access, that dictates food and income available to women and children (Geheb et al. 2008). Declines in fish catch that affect the availability of cash in lakeshore communities thus drive changes in the ways that cash is distributed to and in households. In this way, the commodity at the center of these transactions is broadly generalizable – the resource in decline could be an agricultural commodity, money, or fish.

In contrast, at a wider scale, the processes that shape this particular economy are intimately interwoven with the dynamics of resource extraction and environmental change that set in motion shortfalls in availability. That changes in availability of natural resources precipitate the dynamics we describe above is important because natural resource declines are challenging to reverse and often defy economic expectations. Whereas we might expect fishers to change activities when it becomes more difficult to harvest scarce wildlife, in practice, effort to secure wildlife often increases in the face of scarcity (Cinner 2011; Clark and Lamberson 1982; Mainka and Trivedi 2002; Hutchings and Myers 1995). The feedbacks of wildlife decline thus have the potential to uniquely influence dynamics of jaboya participation and power within relationships.

Positioning the jaboya economy within the broader ecological system has implications not only for appreciating the consequences of resource declines, but for mitigating the interacting ecological, economic, food security and health risks jaboya participants face. In a sense, jaboya relationships are extra-monetary. In both quantitative findings and qualitative descriptions, women’s participation in jaboya relationships is associated with food insecurity. Participation is not, however, associated with monetary factors like household income and assets. Qualitative descriptions further bear out this unique finding in demonstrating the ways power dynamics in sexual relationships, rather than prices alone, respond to small fluctuations in fish availability. Our results have parallels to other literature demonstrating links between food insecurity, economic vulnerability, gendered power dynamics and transactional sex or sex work (McCoy et al. 2014; Chatterji et al. 2005; Cluver et al. 2012; Dunkle et al. 2007; Fielding-Miller et al. 2014; Lwenya and Yongo 2012; Robinson and Yeh 2011). Further, these results position a gendered economy and environmental change as structural drivers of HIV, with parallels to other work on such drivers (Govender et al. 2014; Dworkin et al. 2013; MacPherson et al. 2012) and the roles that persistent food insecurity and poverty play in perpetuating stigma (Tsai et al. 2013) and undermining treatment adherence (Singer et al. 2014; Weiser et al. 2014). While ideas about

! 64 structural factors and engagement in transactional sex have been complicated in an academic literature, the predominant narratives remain focused on economic hardship or opportunistic entrepreneurship to explain women’s motivations for engaging in transactional sex. Yet, the framing of transactional sex and HIV risk solely in microeconomic terms neglects the full context of resource access and the broader political economy in which social and ecological systems shape each other.

The dependence of jaboya relationship dynamics on changes in fish catch and access suggests also that addressing fundamental issues of fish availability and access are critical to addressing jaboya relationships. An important implication of this study is that efforts to advocate behavior change in fishing communities are likely ineffective. Further, that even efforts to increase women’s incomes may not necessarily result in their increased access to fish and power within relationships, especially if fish stocks continue to fall. A deeper understanding of the ways in which jaboya relationships are embedded within the context of fishery ecology permits a consideration of strategies to address not only social but also ecological aspects of the system, and more fundamentally change access to fish and relationship power (e.g. Lowen 2014). Increasing women’s representation in fishery management and co-management and providing opportunities for women to enter more formalized sectors of the fishing economy are promising strategies. More generally, curtailing fishery overharvest and managing for the longevity of healthy fisheries and fishing communities is critical. Of course, these measures are not simple to enact.

Still, acknowledging the complex ecological and social roots of the jaboya economy allows for constructive consideration of these relationships’ functionality and the diverse possible effects of their persistence or termination. The benefits and costs of these types of relationships cannot be categorically assigned; a fish-for-sex exchange presents both risks and opportunities. An analog is offered by the case of widow inheritance, whereby a widow is absorbed into a patrilineal family upon her husband’s death. This has been branded a key factor in the spread of HIV and broadly discouraged. Yet, with appreciation of the role of resources, particularly property rights, widows who are not inherited are now recognized to be at risk of losing rights to land and property, resulting in migration and subsequent vulnerability to HIV (Camlin et al. 2014; Dworkin et al. 2013). The repudiation of widow inheritance does not have simple or summarily beneficial consequences, and, we suggest, much the same can be expected from treatment of jaboya relationships where participants may balance risks of HIV infection with persistent food insecurity and environmental and economic change. Further, although short term fish declines appear to increase HIV risk, long term fish declines may decrease HIV risk as fishers and traders leave the fishery, the fishery drives less migration, and the fishing economy erodes.

Jaboya relationships do not exist in isolation, but rather function within shifting local, regional and global ecologies and their parallel systems of exchange, cooperation and exploitation. In turn, these dynamics determine their ultimate impact for human populations and their natural resources. Changes to the ecological or social systems, be they resource decline or sharp mitigation of jaboya relationships, affect fishing communities and fishery resources.

! 65 Limitations

Conducting this research effort within the context of an on-going research study focused in part on the growth and development of young children biases our sample. We include in both the quantitative and qualitative pieces of this research households where there was a child <2 years in residence. Although our sample represents the preponderance of households in the study region, we do not include the perspectives of men and women past childbearing age, single men and women who do not have a child, and transient fishers and fishmongers who are not in residence in the region. Further, this may explain in part the higher prevalence of men who report engaging in sexual exchanges. Our sample contains all women with a young child, whereas women who do not have a child could be more likely to be unmarried, not have a partner who is a fisher, or participate in sexual exchanges. Although our interview data suggest jaboya relationships and knowledge of others’ participation in these relationships is common, our survey data likely underreports participation in the stigmatized behavior of sexual exchanges, especially for women. The disparity in these findings is likely also due to our targeting of interview participants who acknowledged participation in fish-for-sex relationships and that these participants thus shared perspectives from their own experiences and their work in industries where sexual exchanges are most common. Finally, we use a cross sectional survey and therefore cannot infer causation and our quantitative results cannot necessarily be generalized outside the study community.

6. CONCLUSION

Fish declines have severe consequences for livelihoods and food security, with effects that may also extend much further into traditionally social realms to influence the persistence and power dynamics of a transactional sexual economy. Within Lake Victoria and elsewhere, the world’s poor remain most vulnerable to the consequences of resource declines; galvanizing support to address these declines requires recognition of the full array of social consequences. Researchers and programs concerned with sexual economies and HIV risk must recognize the role of natural resources and environmental change as drivers of social phenomena. The experiences of people reliant on natural resources are embedded in the gendered economies and changing ecologies of the world. When we appreciate the ways people navigate the risks of declining resource access we can improve policy and foster more productive efforts to mitigate the compounding challenges driven by our changing ecosystems.

! 66 Author's personal copy

Fishing for food? Fishing livelihoods and food security

UCB Global Health Framework Program, which was funded by grant Dean’s Research Fellowship (to JMN); UCSF PACCTR and Global 5R25TW7512-3 from the National Institutes of Health (NIH)/Fogarty Health Pathways Research Program (to CRS). This study is published International Center. This work was partly supported by NSF-GEO grant with the permission of the Director, KEMRI. CNH115057; an Andrew and Mary Thompson Rocca Pre-dissertation Fellowship, Sara’s Wish Foundation, National Science Foundation Grad- uate Research Fellowship Program (to KJF); Doris Duke Charitable Conflict of interest The authors declare that they have no conflicts of Foundation International Clinical Research Fellowship (to MDH); UCSF interest.

Appendix

Table 4: Interview Participant Characteristics (n=30) Table 4 Variable definitions and references Number Percentage GenderVariable Type Definition Reference Women 16 53% FishingMen Household Binary Occupation designated14 as fisher47% Food Security Nile perch or tilapia fishing designated as a primary income-earning Secure activity 0 0% Food Security Binary Moderate and severe food insecurity categories: frequency of any Household Food Insecurity Access Scale Mildly Insecure household member 2 taking smaller 7% meals, fewer meals, go to sleep – Q5, 6, 8, 9 (Coates et al. 2007) Moderately Insecure hungry, go a whole7 day and23% night without eating FishSeverely Consumption Insecure Binary Frequency of household21 fish or70% meat consumption; ethnographic Household Demographics experience confirms meat consumption is extremely rare IncomeFisher Only Continuous Past month’s income 9 30% AssetSeller Scale Only Categorical 11-item asset scale 4 13% Asset scale (Vyas and Kumaranayake Fisher and Seller 9 30% 2006); Ethnographic Research Neither Fisher nor Seller 8 27% (Salmen 2009) HousingHousehold Materials Size Categorical (SES) Number of members in the household, binned at upper end EducationIron with Improved Categorical Floor The highest level15 of maternal50% education attained; recorded as some Iron with Natural Floor primary, primary, 4 some secondary,13% etc. AdultImproved Morbidity Floor Binary and WallsCharacterizes whether 1 an adult 3% household member (≥16 years) was too Iron Roof sick to attend 7 work or school23% at least 1 day in the past month MaleAll Morbidity Natural Binary Characterizes whether3 an adult10% male household member (≥16 years) was too sick to attend work or school at least 1 day in the past month Land Ownership Owns 16 53% No Land 14 47% HighestReferences Schooling (Woman) livelihoods and the environment. 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! 78 Chapter'6.'Concluding'Remarks''

We face monumental challenges – to preserve natural resources for food and livelihood uses, maintain biodiversity, solve intractable health problems like malnutrition and HIV, and grapple with troubling gender dynamics and economic forces. Yet these problems are not without solutions. The hope of this work is that illuminating the complexities and trade-offs that shape use of environmental resources and ultimately peoples’ lives will help us to develop better solutions, more conscientious policies, and the commitment to foster changes. Interconnectivity produces both oppositional and synergistic goals. Our challenge is to maximize the synergies and be cognizant of the trade-offs.

An important step in this process is the recognition of the extent to which our natural and social systems are intertwined. In integrating human health and the environment I demonstrate important links between them. In Chapter 2, I show that food-producing livelihoods do not necessarily privilege food access by examining fish consumption among fishing and non-fishing households. In Chapter 3, I expand this work to examine the bounds in time and space of resource availability by analyzing the links between fish harvest and consumption. In Chapter 4, I consider the ways human health impacts the environment, considering in particular the ways households moderate the effects of illness to change fishing behaviors in ways that ultimately increase environmental impact. Finally, in Chapter 5, I examine the ways that declining resource access affects the micro-transactions between men and women by analyzing the effects of fish declines on transactional fish-for-sex relationships.

Households in rural Kenya have been the focus of this study. The ways participant households make use of the environment, the services they get from ecosystems, and their impact on it have been carefully analyzed here. These households are comprised of real people: men, women and children. The people who live in these households will face challenges, but they are hopeful for the future of their community and we should be as well.

These households provide a useful system of study because the links between their health, livelihoods, and environmental reliance are short. Resource reliance for food and livelihoods is measurable because it is direct and salient. The experiences of these households, I hope, widen our perspective about the ways health and the environment are linked – a link friends and colleagues in Kenya often see as self-evident.

Importantly, the experiences of households in a small Kenyan fishing community are emblematic of a much larger group of people. Over 30 million people live in the Lake Victoria basin. Nearly 50% of the world’s population lives in rural areas where social and ecological systems are most closely tied. We all live in a world of finite natural resources. Households grappling with limited resource access, financial constraints, developing economies, and frequent illness often bare the brunt of environmental misuse. Still, the challenges we face are not those of a far away few. The interconnectedness of our trade, ecosystems, and people mean that the challenges of some are challenges of all. Just as the social and natural systems on a small Kenyan island are intertwined, so too are the fates of households across continents.

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