@article{Senia:266536,
      recid = {266536},
      author = {Senia, Mark C. and Dharmasena, Senarath and Todd, Jessica  E.},
      title = {A Complex Model of Consumer Food Acquisitions: Applying  Machine Learning and Directed Acyclic Graphs to the  National Household Food Acquisition and Purchase Survey  (FoodAPS)},
      address = {2018-01-15},
      number = {2015-2018-104},
      series = {Paper 147},
      year = {2018},
      abstract = {Complex causal relationships among a large set of  variables that affect the U.S. households’ food acquisition  and purchase decisions were estimated using machine  learning algorithms and directed acyclic graphs. Asians and  Hispanics live in an environment with high concentrations  of fast- and non-fast food restaurants. Obesity is less  prevalent among Asians. Being Hispanic makes one to be more  food insecure. Those with higher incomes are food secure  and obesity is less prevalent among them. Being Black  positively causes to be a SNAP participant and food  insecure. Obesity is positively caused by fair/poor health  and diet status.},
      url = {http://ageconsearch.umn.edu/record/266536},
      doi = {https://doi.org/10.22004/ag.econ.266536},
}