Researching the influence of market access on rural household nutrition

Daniel Milner
Dan works for the RHoMIS team in Bristol, UK, processing and analysing household survey data to provide insight. He has a background in economic geography and development both in the UK and internationally.

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Editor: We are pleased to welcome a new member to the RHoMIS team, Dan Milner. Joining us at the end of 2019, Dan has already injected fresh energy, expertise and a passion for GIS and data management. In this brief article he shares a little of his background, where he has already used RHoMIS extensively in his Postgraduate studies, as well as what he hopes to achieve in the role.

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​Having joined RHoMIS in December 2019 the past two months have been an energising introduction to the team’s work. In September I completed an MSc in Environmental Policy and Management at Bristol University (more on this in a minute), which is where I first became aware of RHoMIS and the great work the ILRI team are doing. 

As a forward thinking and constantly evolving product, the day-to-day activities of the RHoMIS team always strives towards improvement, increased automation and greater efficiency. This progressive culture has provided a thoroughly enjoyable environment for my role processing and analysing the RHoMIS-generated data.

Prior to joining the team I had the privilege of varied career experiences ranging from farm worker on an agricultural cooperative in northern Spain to Economist at global infrastructure corporation AECOM. 

Tying these disparate activities together is my deep-rooted interest in the nexus of food systems, the environment and economic development that improves outcomes for less advantaged people. Stemming from this, my research interests focus particularly on spatial statistics and the impact of geography on development outcomes. I studied Economics and Geography at undergraduate level in Liverpool before doing an MSc in Economics at Strathclyde University whilst working as an Economist for a regional development agency in the UK. 

After nearly a decade in industry, in 2017 I decided I wanted to up-skill and embarked on a second Masters degree (I’m a sucker for punishment!). For my dissertation, I teamed-up with RHoMIS to investigate how market access influences household dietary diversity in Sub-Saharan African. 

The context within which this question was couched is relatively complex because every household has a different inventory of assets and skills, which results in an often subtle but ultimately infinite range of livelihood strategies.

​Add to the mix the spatially contrasting nature of the surveyed households (as much as 570 km apart) and it becomes clear that any research done in this sphere needs to incorporate a wide range of techniques. ​

RHoMIS surveyed households grouped into 12 clusters using DBSCAN

A Geographical Information Systems (GIS) approach was used along with OpenStreetMaps’ Open Source Route Mapper (OSRM) to calculate the shortest travel times to market from each of the 1,300 RHoMIS households. 
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The clustering algorithm DBSCAN (Density Based Spatial Clustering Application with Noise) was used to group households based on their spatial proximity to each other - the premise for this was based on Tobler’s (1970) first law of geography, “everything is related to everything else, but near things are more related than distant things”. 

Finally, travel time data and clustering allocations were combined with multiple variables from the RHoMIS dataset and modelled using Bayesian probabilistic programming techniques.

​​Findings were not necessarily what I was expecting and improving market access was definitely not found to be a panacea. Some of the headline findings:

• Even with good access to markets, increasing household income does not improve nutrition except when on-farm production is the main source of food stuffs. In this scenario, increasing incomes increases investment in the farm, which in-turn improves nutrition. The income-nutrition relationship turned out to be a classic ecological fallacy scenario.
• ‘Travel time to market’ is not an effective proxy for ‘market access’ but ‘walking time to the nearest road’ is, which makes sense given the pertinence of travelling salesman and farm-gate sales.
• The relationship between market access and nutrition is not linear. Instead, there emerged three farm typologies:
  
  1. Large farms with low crop diversity would benefit most from improved market access.
     
  2. Small farms that are geographically close to physical markets would benefit from having more space and being able to produce more food on the farm.
     
  3. Farms that are far away from physical markets but have good access to roads would benefit most from increasing the variety of crops grown on the farm.

Overall, its seems the optimum formula for a rural household is to cultivate between 1 and 2 ha, grow a mixture of commercial crops and crops for home consumption, be located between 5 and 10 minute walk to a road and within 20 minutes drive to a physical market.

I thoroughly enjoyed the dissertation process and I am very much looking forward to the year ahead working with the team and getting to know more of the RHoMIS community of practice. Please feel free to contact me via email here.

​Select references:

• Arcaya M., (2012) Area Variations in health: A Spatial Multilevel Modelling Approach, Health & Place, 18(4), 824-831. 
• Chamberlain J., Jayne T., (2011) Unpacking the Meaning of “Market Access”, World Development, 41(C), 245-264. 
• Ellis F., (1998) Household Strategies and Rural Livelihood Diversification, Journal of Development Studies, 35(1), 1-38. 

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