Background: Continuous glucose monitors (CGM) are used to characterize postprandial glycemia, yet no study has directly tested how different test foods/beverages alter CGM accuracy.
Objectives: Assess glycemic responses to test foods/drinks using CGM compared with capillary sampling (criterion).
Methods: Fifteen healthy females (n = 9) and males (n = 6) completed 7 laboratory visits in a randomized crossover design with ≥48 h washout between visits. During each visit, participants consumed an oral carbohydrate challenge comprising either 50 g glucose or equivalent 50 g carbohydrate as whole fruits, 50 g carbohydrate as blended fruit, 50 g carbohydrate as commercially available fruit smoothie, 50 g carbohydrate as commercially available fruit smoothie ingested over 30 ± 4 min, 50 g carbohydrate as commercially available fruit smoothie with 5 g inulin, 30 g carbohydrate as commercially available fruit smoothie. The glycemia was recorded from both CGM and capillary samples every 15 min for 120 min and expressed as incremental areas under the curve. The glycemic index (GI) was calculated relative to 50 g glucose where appropriate. Exploratory analyses examined 1) interindividual heterogeneity of CGM bias compared with criterion and 2) whether CGM bias could be improved with adjustment for baseline differences.
Results: CGM-estimated fasting and postprandial glucose concentrations were (mean ± standard deviation) 0.9 ± 0.6 and 0.9 ± 0.5 mmol/L higher than capillary estimates, respectively(both, P < 0.001). CGM bias varied by postprandial test such that GI for 50 g carbohydrate as commercially available fruit smoothie was higher with CGM (69; 95% confidence interval: 48, 99) compared with capillary (53; 95% confidence interval: 40, 69; P = 0.05). Furthermore, differences in CGM compared with capillary fasting glucose concentrations varied by participant (P = 0.001). Unadjusted, CGM overestimated time >7.8 mmol/L by ∼4-fold, and adjustment for baseline differences reduced this overestimate to ∼2-fold (both P < 0.01).
Conclusions: CGM overestimated glycemic responses in numerous contexts. At times, this can mischaracterize the GI. In addition, there is interindividual heterogeneity in the accuracy of CGM in estimating fasting glucose concentrations. Correction for this difference reduces, but does not eliminate, postprandial overestimate of glycemia by CGM. Caution should be applied when inferring absolute or relative glycemic responses to foods using CGM, and capillary sampling should be prioritized for accurate quantification of glycemic response. This trial was registered at clinicaltrials.gov as NCT06333184.
Background: There is no specific dietary pattern for cardiometabolic health based on Chinese food culture.
Objectives: The study aimed to develop and assess the efficacy of the reducing cardiometabolic disease risk (RCMDR) dietary pattern on cardiometabolic disease risk in the Chinese population with dyslipidemia.
Methods: In this single-center, open-label, randomized, 12-wk dietary intervention study, 100 adults aged 35-45 y with dyslipidemia were randomly assigned (1:1) to the RCMDR dietary pattern intervention or general health education control group.
Results: Compared with the control group, the RCMDR dietary pattern intervention resulted in a significantly lower clustered cardiometabolic risk score (primary outcome) (β: -0.17; 95% CI: -0.29, -0.05); diastolic blood pressure (β: -0.23; 95% CI: -0.40, -0.07); total cholesterol, LDL cholesterol, triglyceride (β: -0.27; 95% CI: -0.49, -0.04; β: -0.24; 95% CI: -0.41, -0.07; and β: -0.19; 95% CI: -0.35, -0.04, respectively); homocysteine (β: -0.19; 95% CI: -0.28, -0.09); waist circumference, waist-to-hip ratio, body fat percentage, body fat mass, visceral adipose tissue, visceral fat area, and a significantly higher lean body mass (β: -1.12; 95% CI: -1.65, -0.59; β: -1.01; 95% CI: -1.66, -0.36; β: -1.43; 95% CI: -1.87, -0.98; β: -0.98; 95% CI: -1.35, -0.60; β: -1.93; 95% CI: -2.75, -1.11; β: -6.52; 95% CI: -9.10, -3.95; and β: 1.24; 95% CI: 0.84, 1.65, respectively).
Conclusions: Compared with the control group, the RCMDR dietary pattern intervention lowers cardiometabolic risk, blood lipids, blood pressure, abdominal obesity, and circulating homocysteine concentration among Chinese population with dyslipidemia.
Clinical trial registry: This trial was registered at Chinese Clinical Trial Registry as ChiCTR2300072472 (https://www.chictr.org.cn/showproj.html?proj=198618).
Background: The 2018 World Cancer Research Fund/American Institute for Cancer Research Third Expert Report, including studies up to 2015, determined limited-no conclusion evidence on dietary patterns and colorectal cancer (CRC) risk due to insufficient data and varying pattern definitions.
Objectives: This updated review synthesized literature on dietary patterns and CRC risk/mortality.
Methods: PubMed and Embase were searched through 31 March, 2023, for randomized controlled trials (RCTs) and prospective cohort studies on adulthood dietary patterns. Patterns were categorized by derivation method: a priori, a posteriori, or hybrid, and were then descriptively reviewed in relation to the primary outcomes: CRC risk or mortality. The Global Cancer Update Programme Expert Committee and Expert Panel independently graded the evidence on the likelihood of causality using predefined criteria.
Results: Thirty-two dietary scores from 53 observational studies and 3 RCTs were reviewed. Limited-suggestive evidence was concluded for higher alignment with a priori-derived patterns: Mediterranean, healthful plant-based index, Healthy Eating Index (HEI)/alternate HEI, and Dietary Approaches to Stop Hypertension (DASH), in relation to lower CRC risk. Common features across these diets included high plant-based food intake and limited red/processed meat. Hybrid-derived patterns: the empirical dietary pattern for hyperinsulinemia and empirical dietary inflammatory pattern (EDIP), showed strong-probable evidence for increased CRC risk. Evidence for a priori-derived low-fat dietary interventions and a posteriori-derived patterns was graded as limited-no conclusion. By cancer subsite, higher alignment with Mediterranean diet showed limited-suggestive evidence for lower rectal cancer risk, and that with HEI/alternate HEI and DASH showed limited-suggestive evidence for lower colon and rectal cancer risks. Empirical dietary pattern for hyperinsulinemia and EDIP showed strong-probable evidence for increased colon cancer risks. All exposure-mortality pairs and other pattern-outcome associations were graded as limited-no conclusion.
Conclusions: This review highlights the role of dietary patterns in CRC risk/mortality, providing insights for future research and public health strategies. This review was registered at PROSPERO as CRD42022324327 (https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022324327).