Social Vulnerability as a Predictor of Farmer Stress
Abstract
Background
The Social Vulnerability Index (SVI) was developed for use in disaster preparedness and relief efforts. As an aggregate measure of community vulnerability, it could potentially be functional in other contexts as well. Furthermore, its components of socioeconomic status, household characteristics, racial and ethnic minority status, and housing type and transportation have similar potential applications. In this study, we are testing its application as a predictor of mental health in agricultural workers. Considering research has also established that Farmers in Georgia are disproportionately impacted by stress and suicidal ideation, we seek to better understand if SVI and its components are useful tools in predicting mental health outcomes in farmers.
Methods
County-level SVI data were acquired from publicly available CDC archives for the year 2020 (most recent available). Data on Georgia farmworker stress, suicidality, and demographics were obtained from the Farmer’s Mental Well-Being Study conducted in the spring of 2022. Multiple linear regression and logistic regression were used to determine the relationship between SVI and the SVI subscales and the outcomes of stress and suicidal ideation. Common demographics known to correlate with outcome variables were controlled for.
Results
In our poster we present full findings from our regression models including odds ratios for each predictor as well as overall model fit.
Conclusion
Farmworker well-being is a complex issue with many contributing factors. Work outlining community characteristics that contribute to negative mental health outcomes for farmers is one important part of the bigger picture. Continued work to determine how existing indices and tools are applicable to the epidemiology of farmer wellbeing is needed.
Keywords
Rural Health, Farmer, Stress, Suicide, Mental Health
Social Vulnerability as a Predictor of Farmer Stress
Background
The Social Vulnerability Index (SVI) was developed for use in disaster preparedness and relief efforts. As an aggregate measure of community vulnerability, it could potentially be functional in other contexts as well. Furthermore, its components of socioeconomic status, household characteristics, racial and ethnic minority status, and housing type and transportation have similar potential applications. In this study, we are testing its application as a predictor of mental health in agricultural workers. Considering research has also established that Farmers in Georgia are disproportionately impacted by stress and suicidal ideation, we seek to better understand if SVI and its components are useful tools in predicting mental health outcomes in farmers.
Methods
County-level SVI data were acquired from publicly available CDC archives for the year 2020 (most recent available). Data on Georgia farmworker stress, suicidality, and demographics were obtained from the Farmer’s Mental Well-Being Study conducted in the spring of 2022. Multiple linear regression and logistic regression were used to determine the relationship between SVI and the SVI subscales and the outcomes of stress and suicidal ideation. Common demographics known to correlate with outcome variables were controlled for.
Results
In our poster we present full findings from our regression models including odds ratios for each predictor as well as overall model fit.
Conclusion
Farmworker well-being is a complex issue with many contributing factors. Work outlining community characteristics that contribute to negative mental health outcomes for farmers is one important part of the bigger picture. Continued work to determine how existing indices and tools are applicable to the epidemiology of farmer wellbeing is needed.
