The purpose of this study is to determine if renal function varies by metabolic phenotype. A total of 9599 patients from a large Federally Qualified Health Center (FQHC) were included in the analysis. Metabolic health was classified as the absence of metabolic abnormalities defined by the National Cholesterol Education Program Adult Treatment Panel III criteria, excluding waist circumference. Obesity was defined as body mass index >30 kg/m2 and renal health as an estimated glomerular filtration rate (eGFR) >60 mL/min/1.732. Linear and logistic regressions were used to analyze the data. The metabolically healthy overweight (MHO) phenotype had the highest eGFR (104.86 ± 28.76 mL/min/1.72m2) and lowest unadjusted odds of chronic kidney disease (CKD) (OR = 0.46, 95%CI = 0.168, 1.267, p = 0.133), while the metabolically unhealthy normal weight (MUN) phenotype demonstrated the lowest eGFR (91.34 ± 33.28 mL/min/1.72m2) and the highest unadjusted odds of CKD (OR = 3.63, p < 0.0001). After controlling for age, sex, and smoking status, the metabolically unhealthy obese (MUO) (OR = 1.80, 95%CI = 1.08, 3.00, p = 0.024) was the only phenotype with significantly higher odds of CKD as compared to the reference. We demonstrate that the metabolically unhealthy phenotypes have the highest odds of CKD compared to metabolically healthy individuals.

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Physical activity is essential to maintain physical and mental well-being. During the COVID-19 pandemic, in-person physical activity opportunities were limited. This paper describes a telephone-based physical activity support strategy among racially/ethnically diverse patients during the COVID-19 pandemic. Adult patients at a large, Federally Qualified Health Center with an on-site exercise facility referral were eligible to transition to telephone support with personal fitness advisors during the pandemic stay-at-home orders. Baseline surveys assessed physical activity and environmental characteristics; follow-up phone calls used motivational interviewing and physical activity goal setting strategies. From March 23-July 23, 2020, 72 patients participated in 270 phone calls, or 3.8 (±2.1) calls per participant. Participants were, on average, aged 51.3 (±11.6) years, 87.5% female, 31.9% Hispanic/Latino, and 47.2% non-Hispanic Black. Patients meeting physical activity guidelines pre-pandemic reported more planned exercise (100.0% vs. 55.3%; p<0.001), exercise days at home (5.0 vs. 1.7; p<0.001), and accomplishment of personal physical activity goals (57.0% vs. 39.7%; p = 0.11) than patients not meeting guidelines pre-pandemic. Patients with a home treadmill participated in twice the rate of calls compared to those without (RR = 2.22; 95%CI:1.35,3.64), but no other home environmental characteristics predicted participation rate. Pre-pandemic physical activity behavior appeared to predict pandemic physical activity and telephone-based physical activity support was effective for maintaining physical activity for some participants. Long term applications of this work will support continuity of clinic-community partnerships for health behavior change and provide a model for patient physical activity support by community health centers without on-site exercise facilities.