Background

Food insecurity is associated with increased adiposity, obesity-related comorbidities, and lower socioeconomic status. Body composition is commonly measured by bioelectrical impedance; however, artificial intelligence now allows for computed tomography (CT)-based analytical techniques. We hypothesize that food insecurity affects baseline body composition and bariatric surgery outcomes.

Methods

Fifty-four patients completed a six-item food security survey and underwent abdominal CT prior to bariatric surgery at a single center from 2018-2019. Patients were grouped as either low/very low or high/marginal food security. Body composition analyses were performed using an automated high throughput, CT-based algorithm to calculate cross-sectional area of skeletal muscle, visceral fat, and subcutaneous fat (Figure 1). Each patient was matched to previously constructed reference curves by age, sex, and race to generate a z score. Patient characteristics and six-month outcomes were compared by t test and chi square.

Results

In both groups, subcutaneous and visceral fat area were increased compared to population reference curves (p<0.05). The 14 (26%) patients who experienced low/very low food security had lower skeletal muscle area and higher subcutaneous fat area (p<0.05) than patients without food insecurity (Table 1). The two groups had similar weight loss and reduction in obesity-related medications following bariatric surgery.

Conclusions

Patients with obesity and food insecurity have less skeletal muscle and more subcutaneous fat than those without food insecurity. Despite this, bariatric surgery remains similarly effective regardless of food security, making it a powerful tool for improving the health of patients with obesity with food insecurity and lower socioeconomic status.