Emerson, Sam R.2017-05-302017-05-302017-08-01http://hdl.handle.net/2097/35605The aims of this dissertation were to provide innovative, applicable insights regarding the impact of single-meal consumption on metabolic and inflammatory responses in the acute post-meal (“postprandial”) period. In Chapter 2, the connection between large postprandial glucose and triglyceride (TG) fluxes and cardiovascular disease (CVD) risk were reviewed. A new marker of metabolic status, Metabolic Load Index (MLI), calculated by adding glucose and TG, was proposed based on several considerations: 1) independent associations between postprandial glucose and TG with CVD risk, although the substrates are considered to increase risk through similar mechanisms; 2) postprandial glucose and TG responses are interrelated; and 3) meals consumed in daily life typically contain both carbohydrate and fat. MLI may be useful in characterizing metabolic status/risk in both clinical and research settings. Chapter 3 was a systematic review with the purpose of objectively describing postprandial responses (i.e. magnitude and timing) to a high-fat meal (HFM) in five commonly assessed inflammatory markers: interleukin (IL)-6, C-reactive protein (CRP), tumor necrosis factor (TNF)-α, IL-1β, and IL-8. IL-6 increased in >70% of studies, starting at ~1.4 pg/mL pre-meal and peaking at ~2.9 pg/mL ~6 hours post-HFM. Other markers (CRP, TNF-α, IL-1β, and IL-8) did not change after the HFM in the majority of studies. These findings suggest that IL-6 is an inflammatory marker that routinely increases following HFM consumption. Future postprandial studies should further investigate IL-6, as well as explore novel markers of inflammation. In Chapter 4, we compared the metabolic and inflammatory responses to a HFM (17 kcal/kg, 60% fat), representative of meals used in previous postprandial studies, to two meal trials that were more reflective of typical eating patterns: a moderate-fat meal (MFM; 8.5 kcal/kg, 30% fat), and a biphasic meal (BPM), in which the MFM was consumed twice, three hours apart. The HFM elicited a greater total area-under-the-curve (tAUC) TG response (1348.8 ± 783.7 mg/dL x 6 hrs) compared to the MFM (765.8 ± 486.8 mg/dL x 6 hrs; p = 0.0005) and the BPM (951.8 ± 787.7 mg/dL x 6 hrs; p = 0.03), but the MFM and BPM were not different (p = 0.72). It appears that the large postprandial TG response observed in previous studies may not be representative of the daily metabolic challenge for many individuals. Chapter 5 assessed the impact of both aging and chronic physical activity level on postprandial metabolic responses by comparing three groups: younger active (YA), older active (OA), and older inactive (OI) adults. The TG tAUC response was lower in YA (407.9 ± 115.1 mg/dL x 6 hr) compared to OA (625.6 ± 169.0 mg/dL x 6 hr; p = 0.02) and OI (961.2 ± 363.6 mg/dL x 6 hr; p = 0.0002), while the OA group TG tAUC was lower than OI (p = 0.02). Thus, it is likely that both aging and chronic physical activity level impact the postprandial metabolic response. This series of projects provides needed clarification regarding the postprandial metabolic and inflammatory responses to single-meal intake, particularly in the context of real-life application.en-USPostprandialMetabolismInflammationTriglyceridesAgingPhysical activityDissertation