Food security and well-being among older, rural Americans before and during the COVID-19 pandemic

Abstract

The COVID-19 pandemic has impacted many aspects of our lives. Older adults, those with less income or fewer resources, and those living in rural parts of the United States are potentially more vulnerable. To understand the negative impact of COVID-19 on perceived food security, physical and mental health, and loneliness in a sample of older, rural, low-income adults in the United States, we use results from a mailed survey in which residents of four Indiana counties contrasted their status during the early period of the pandemic to their typical pre-pandemic status. We test for significant changes in status and what predicts negative impacts to food security, health, and loneliness. We asked respondents to report on both pre-pandemic and since-pandemic experiences in the instrument, which was administered after the pandemic had begun, in May 2020. We measure food security using the U.S. Household Food Security Survey Module (six-item short form; HFSSM), physical and mental health using the Centers for Disease Control's Healthy Days Measures (HRQOL-4), and loneliness using the UCLA Revised Loneliness Scale. A binomial test identified significant declines in status for all three measures. Logistic regressions identified factors associated with each of the measures worsening. Fear of going to the store or food pantry was associated with all three measures. Decreased store hours and closed food pantries were associated with lower food security. More education, fewer years of age, being female, decreased income, and stockpiling were associated with more reported days of poor physical or mental health. Fewer years of age, lack of transportation, and eating less often with others were associated with perceived increased loneliness. The pandemic had a negative impact on respondents' food security, unhealthy days, and loneliness, but different factors were associated with each measure for this population. Our findings provide insight for targeted recovery efforts.

Fig 1. Descriptive statistics for pandemic-related variables used in the models.