Where do tobacco farmers live: association between Kenyan tobacco farmers' livelihood selection decision and their accessibility to nearby economic centers

摘要

Background: Prosperous economic livelihood described by industry is hallucination in Kenya, smallholder tobacco farmers are making small or no profits [1-4]. World Health Organization Framework Convention on Tobacco Control (WHO FCTC) Article 17 encourages viable alternative livelihoods for tobacco farmers. However, little evidence on how tobacco farmers make livelihood selection decisions exists. [5] Therefore, we examined tobacco farmers' livelihood selection decisions under different accessibility levels to nearby economic centers. Methods: 527 smallholder tobacco farmers in Kenya from three main tobacco-growing regions participated in our 2016-2017 wave economic livelihood survey, among whom 345 participants are current growers and 287 have a partnership contract. Geo-economic data was matched to surveyed farmers' Global Positioning System (GPS) coordinates to estimate each farmer's objective access to nearby economic centers. We examined the association between access to nearby economic centers and farmers' choice to grow tobacco and to grow tobacco under contract. Multivariate logistic regressions were adopted for models while controlling for social-economic status and self-reported activity in nearby economic centers. We also examined these models with regional variables fixed. Results: Tobacco farmers rarely live within 10 kilometers range of an economic center. Farmers living 15-19.99 kilometers away from economic centers are 80.4% to 81.3% less likely to grow tobacco compared to those who live 10-14.99 kilometers away, and farmers living more than 20 kilometers away are 56.5% to 89.1% less likely to grow. Tobacco farmers living more than 20 kilometers away are 4.2 to 18.5 times more likely to grow under contract. Conclusions: Farmers living further away from an economic center is less likely to grow tobacco, but if they grow tobacco, they are much more likely to grow under contract. The identification of geographic heterogeneity not only reveals the spatial economic dynamics, but also helps policy makers tailoring policies at different regional level.