J. C. Hurwitz1, A. J. Polis2, V. Santos3, C. Mendez4, A. Sanchez5, D. Zhang6, A. Katz7, T. J. Carpenter3, J. A. Haas3, and J. W. Lischalk3; 1Department of Radiation Oncology, New York University Long Island School of Medicine, Mineola, NY, 2Department of Radiation Oncology, New York University Grossman Long Island School of Medicine, Mineola, NY, 3Department of Radiation Oncology, Perlmutter Cancer Center at New York University Langone Hospital - Long Island, Mineola, NY, 4Department of Radiation Oncology, Perlmutter Cancer Center, NYU Long Island, Mineola, NY, 5NYU Langone Health - Long Island, Mineola, NY, United States, 6Department of Foundations of Medicine, New York University Grossman Long Island School of Medicine, Mineola, NY, 7Department of Urology, Perlmutter Cancer Center at New York University Langone Hospital - Long Island, Mineola, NY
Purpose/Objective(s): Clinical factors known to affect PSA include age, BMI, diabetes mellitus (DM), BPH, smoking, and medications. While diet has been linked to PSA, the impact of food insecurity remains unexplored. This study evaluates an expanded role for sociodemographic factors including food insecurity in interpreting Prostate Cancer (PCa) screening PSA. Materials/
Methods: In this cross-sectional analysis of NHANES 2005-2006 and 2007-2008, we identified men age >40 years with PSA values and food insecurity screening, excluding subjects with PCa history or recent prostate intervention. Food insecurity was assessed via a validated two-item screen. Mann-Whitney, Kruskal-Wallis, and Spearman’s correlation testing were used to investigate association with PSA levels and free PSA ratio. Multivariable linear regression was used to analyze factors found significant on univariable analysis. Secondary analysis evaluated contributing factors to food insecurity using logistic regression. Results: We studied 2942 NHANES subjects with mean age 59.6 years (SD 12.7) and BMI 28.8 kg/m2 (SD 5.8). Most (54%) identified as non-Hispanic White with the remainder as Black (20%), Mexican American (16%), other Hispanic (7%), and other race (3%). Comorbidities included BPH (17%) and DM (16%). A minority (20%) were daily smokers. Medication use included five-alpha reductase inhibitors (5ARIs) (2%), alpha blockers (7%), testosterone (<1%), statins (25%), and thiazides (11%). Finally, 18% of the cohort screened positive for food insecurity, and mean total PSA was 1.9ng/ml (SD 3.3) with mean free PSA ratio 29.9% (SD 12.1). On univariable analysis, food insecurity, as well as selenium, lycopene, and beta carotene intake were significantly associated with total PSA. However, on multivariable analysis, only age (fold change [FC] 1.14, p<0.01, units = 5 years), BMI (FC 0.95, p<0.01, units = 5 kg/m2), Black identity (FC 1.22, p<0.01), Mexican American identity (FC 1.17, p<0.01), BPH (FC 1.25, p<0.01), 5ARIs (FC 0.57, p<0.01), and statins (FC 0.90, p=0.02) were significantly associated with total PSA. Similarly, age, Black identity, Mexican American identity, other Hispanic identity, DM, BPH, family history of PCa, smoking, and statins were significantly associated with free PSA ratio. On multivariable secondary analysis, age, race and ethnicity, education level, family income, and smoking were significantly associated with food insecurity. Conclusion: In this first analysis of its kind, we do not demonstrate a distinct association between food insecurity and PSA. However, we do show significant associations between clinical and sociodemographic factors with both PSA and food insecurity. The link between food insecurity and PSA may be explained by these factors or may be due to our inability to distinguish between temporary and chronic food insecurity. Further investigation to better understand the nuances of multifactorial patient characteristics and PSA is warranted.
