RESUMO
Background: Sedentary behavior (SB) is detrimental to cardiometabolic disease (CMD) risk, which can begin in young adulthood. To devise effective SB-CMD interventions in young adults, it is important to understand which context-specific sedentary behaviors (CS-SB) are most detrimental for CMD risk, the lifestyle behaviors that co-exist with CS-SBs, and the socioecological predictors of CS-SB. Methods: This longitudinal observational study will recruit 500 college-aged (18-24 years) individuals. Two laboratory visits will occur, spaced 12 months apart, where a composite CMD risk score (e.g., arterial stiffness, metabolic and inflammatory biomarkers, heart rate variability, and body composition) will be calculated, and questionnaires to measure lifestyle behaviors and different levels of the socioecological model will be administered. After each visit, total SB (activPAL) and CS-SB (television, transportation, academic/ occupational, leisure computer, "other"; ecological momentary assessment) will be measured across seven days. Discussion: It is hypothesized that certain CS-SB will show stronger associations with CMD risk, compared to T-SB, even after accounting for coexisting lifestyle behaviors. It is expected that a range of intra-individual, inter-individual, and physical environment socioecological factors will predict CS-SB. The findings from this study will support the development of an evidence-based, multi-level intervention to target SB reduction and mitigate CMD risk in CBYA.
RESUMO
OBJECTIVE: To explore the feasibility of screening for type 2 diabetes (T2DM) and the prevalence of adult patients seen in a dental clinic at risk for T2DM based on American Diabetes Association (ADA) diabetes risk test (DRT) scores and point of care hemoglobin A1C (A1C) values. METHOD AND MATERIALS: This was a cross-sectional analysis of data from adults 18 to 89 years old seen in an academic dental clinic between November 2019 and April 2022 without prior history of diabetes. Clinical and demographic data were obtained from electronic health records and odontograms. Frequency distributions, chi-square, and Mann-Whitney U tests were used for data analysis. RESULTS: Of the 13,519 patients whose data were included, 54.7% (n = 7,389) were women. Of those with race and ethnicity data, 53.6% (n = 2,871) were white, 40.2% (n = 2,153) were African American, and 29.5% (n = 1,559) were Hispanic/Latino. Mean ± SD age was 47.0 + 17.0 years; mean ± SD body mass index was 28.0 ± 6.1 kg/m2. Thirty-five percent (n = 4,774) had diabetes risk test scores reflecting T2DM risk. Those at risk were more likely to be older, male, and overweight/obese than those not at risk (P < .001). Of those at risk who consented to a point of care A1C (9.8%, n = 470), 40.2% (n = 189) had values consistent with dysglycemia (A1C ≥ 5.7%); 34.9% (n = 164) reflecting prediabetes (A1C = 5.7% to 6.4%) and 5.3% (n = 25) diabetes (A1C ≥ 6.5%). CONCLUSIONS: Diabetes screening in a dental clinic identified that over one-third of adults without T2DM were at risk based on diabetes risk test scores. Of those who had point of care A1Cs conducted; 40% had dysglycemia. Diabetes screening in an academic dental clinic can help identify patients at risk for T2DM.
