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PURPOSE: Investigating the impact of social determinants of health (SDOHs) on cancer care in large populations relies on census estimates. Routine clinic SDOH screening provides timely patient-level information which could inform best practices. This study evaluated the correlation between patient-reported SDOH needs and population-level census tract measures. METHODS: This was a retrospective cross-sectional study of a cohort of adult patients with GI malignancy screened for SDOHs such as financial insecurity, transportation, and food insecurity during initial outpatient evaluation at East Carolina University (formerly Vidant) Health Medical Center in Greenville, NC (November 2020-July 2021). Primary outcomes included number and severity of identified SDOH needs and area deprivation index (ADI) and census tract measures for each patient. Spearman rank correlations were calculated among patient-level needs and between patient-level needs and similar census tract measures. RESULTS: Of 112 patients screened, 58.9% self-identified as White (n = 66) and 41.1% as Black (n = 46). A total of 50.5% (n = 54) resided in a rural county. The collective median state ADI rank was 7 (IQR, 5-9). The median household income was $38,125 in US dollars (USD) (IQR, $31,436-$48,934 [USD]). Only 12.5% (n = 14) reported a moderate or severe financial need. Among reported needs, financial need moderately correlated with food insecurity (coefficient, 0.46; P < .001) and transportation (coefficient, 0.45; P < .001). Overall, census tract measures and reported needs poorly correlated. Lack of transportation correlated with percentage of households without a vehicle (coefficient, 0.18; P = .03) and limited access to healthy foods (coefficient, 0.18; P = .04). CONCLUSION: Given the poor correlation between reported and census needs, population-level measures may not accurately predict patient-reported needs. These findings highlight the importance of SDOH screening in the clinical setting to reduce health disparities and identify opportunities to improve care delivery.
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BACKGROUND: A fluorochemical facility near Fayetteville, North Carolina, emitted per- and polyfluoroalkyl ether acids (PFEAs), a subgroup of per- and polyfluoroalkyl substances (PFAS), to air. OBJECTIVE: Analyze PFAS in private wells near the facility and in blood from well users to assess relationships between PFEA levels in water and serum. METHODS: In 2019, we recruited private well users into the GenX Exposure Study and collected well water and blood samples. We targeted 26 PFAS (11 PFEAs) in water and 27 PFAS (9 PFEAs) in serum using liquid chromatography-mass spectrometry. We used regression modeling to explore relationships between water and serum PFAS. For the only PFEA detected frequently in water and serum, Nafion byproduct 2, we used generalized estimating equation (GEE) models to assess well water exposure metrics and then adjusted for covariates that may influence Nafion byproduct 2 serum concentrations. RESULTS: We enrolled 153 participants ages 6 and older (median = 56 years) using 84 private wells. Most wells (74%) had ≥6 detectable PFEAs; median ∑PFEAs was 842 ng/L (interquartile range = 197-1760 ng/L). Low molecular weight PFEAs (PMPA, HFPO-DA [GenX], PEPA, PFO2HxA) were frequently detected in well water, had the highest median concentrations, but were not detectable in serum. Nafion byproduct 2 was detected in 73% of wells (median = 14 ng/L) and 56% of serum samples (median = 0.2 ng/mL). Cumulative dose (well concentration × duration at address) was positively associated with Nafion byproduct 2 serum levels and explained the most variability (10%). In the adjusted model, cumulative dose was associated with higher Nafion byproduct 2 serum levels while time outside the home was associated with lower levels. IMPACT: PFAS are a large class of synthetic, fluorinated chemicals. Fluorochemical facilities are important sources of environmental PFAS contamination globally. The fluorochemical industry is producing derivatives of perfluoroalkyl acids, including per- and polyfluoroalkyl ether acids (PFEAs). PFEAs have been detected in various environmental samples but information on PFEA-exposed populations is limited. While serum biomonitoring is often used for PFAS exposure assessment, serum biomarkers were not good measures of long-term exposure to low molecular weight PFEAs in a private well community. Environmental measurements and other approaches besides serum monitoring will be needed to better characterize PFEA exposure.