TY - JOUR
T1 - How are Income and Assets Associated with Food Insecurity? An Application of the Growth Mixture Modeling
AU - Chen, Jun Hong
AU - Wu, Chi Fang
AU - Jin, Minchao
N1 - Funding Information:
This research is a secondary data analysis study not supported by external funds. The authors wish to acknowledge all the individuals who played a key role in the development and implementation of the Panel Study of Income and Dynamics (PSID).
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature B.V.
PY - 2023/2
Y1 - 2023/2
N2 - Food insecurity remains prevalent in the United States, affecting millions of households. Research has confirmed that low income and limited assets are risk factors for food insecurity, but how income and assets are associated with food insecurity has not been fully explored in light of the fact that food insecurity endures or worsens over time for some people but not others. Using 2015, 2017, and 2019 waves of the panel study of income dynamics, this study (1) investigated the heterogeneity of food insecurity trajectories using Growth Mixture Modeling; (2) performed a multinomial logistic regression to examine how income and assets are associated with the relative risk of facing a more severe food insecurity trajectory; and (3) compared the coefficient of income with the coefficient of assets. Results of this study showed that both higher income and more assets are associated with a lower probability of facing food insecurity that worsens rather than improves with time. This study also observed that the association strength was stronger for income than for assets. These results offer insights for policies aimed at creating efficient financial support strategies (e.g., income assistance, asset building) that reduce recipients’ risk of experiencing long-term food insecurity.
AB - Food insecurity remains prevalent in the United States, affecting millions of households. Research has confirmed that low income and limited assets are risk factors for food insecurity, but how income and assets are associated with food insecurity has not been fully explored in light of the fact that food insecurity endures or worsens over time for some people but not others. Using 2015, 2017, and 2019 waves of the panel study of income dynamics, this study (1) investigated the heterogeneity of food insecurity trajectories using Growth Mixture Modeling; (2) performed a multinomial logistic regression to examine how income and assets are associated with the relative risk of facing a more severe food insecurity trajectory; and (3) compared the coefficient of income with the coefficient of assets. Results of this study showed that both higher income and more assets are associated with a lower probability of facing food insecurity that worsens rather than improves with time. This study also observed that the association strength was stronger for income than for assets. These results offer insights for policies aimed at creating efficient financial support strategies (e.g., income assistance, asset building) that reduce recipients’ risk of experiencing long-term food insecurity.
KW - Assets
KW - Food insecurity
KW - Food insecurity trajectory
KW - Growth Mixture Modeling
KW - Heterogeneity
KW - Income
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U2 - 10.1007/s11205-022-03053-x
DO - 10.1007/s11205-022-03053-x
M3 - Article
AN - SCOPUS:85145229722
SN - 0303-8300
VL - 165
SP - 959
EP - 973
JO - Social Indicators Research
JF - Social Indicators Research
IS - 3
ER -