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.
Objective: The study aimed to develop and assess the efficacy of the Reducing Cardiometabolic Diseases Risk (RCMDR) dietary pattern on cardiometabolic risk in the Chinese population with dyslipidemia.
Methods: In this single-center, open-label, randomized, 12-week dietary intervention study, 100 adults aged 35-45 years with dyslipidemia were randomized (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, low-density lipoprotein cholesterol, triglyceride (β = -0.27; 95% CI -0.49, -0.04; β = -0.24; 95% CI -0.41, -0.07; β = -0.19; 95% CI -0.35, -0.04); homocysteine (Hcy) (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; β = 1.24; 95% CI 0.84, 1.65).
Conclusions: Compared to the control group, the RCMDR dietary pattern intervention lowered cardiometabolic risk, blood lipids, blood pressure, abdominal obesity and circulating Hcy level among Chinese population with dyslipidemia.
Clinical trial registry number and website: Chinese Clinical Trial Registry (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).
Background: Diet and genetic risk are risk factors for colorectal cancer (CRC). The interaction between the EAT (Lancet Commission on healthy diets from sustainable food systems)-Lancet diet and genetic variants on CRC risk remains unclear.
Objectives: We aim to investigate the association between EAT-Lancet diet and CRC risk and to evaluate its combined effect with genetic risk on CRC risk.
Methods: We conducted a prospective cohort study involving 177,441 participants from the UK Biobank who completed 24-h food recall questionnaires at least once. The EAT-Lancet Diet Index (ELD-I) was calculated using the dietary recall data to assess EAT-Lancet diet, and a polygenic risk score (PRS) was constructed by using 197 single-nucleotide polymorphisms to evaluate genetic risk. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression models to assess the associations.
Results: During a median follow-up of 13.05 y, 2,016 participants developed CRC. Higher ELD-I was significantly associated with a reduced CRC risk (the highest compared with the lowest HR: 0.87, 95% CI: 0.76-0.99). A significant additive interaction between PRS and ELD-I was identified on CRC risk (relative excess risk due to interaction: 0.142, 95% CI: 0.058, 0.225). The ELD-I was significantly associated with reduced CRC risk in individuals with moderate but not low and high genetic risk, with HRs (95% CIs) of 0.76 (0.63, 0.92), 0.84 (0.53, 1.33), and 0.96 (0.76, 1.20), respectively. Compared with participants with higher PRS and lower ELD-I, those with lower PRS and higher ELD-I showed a 75% reduction in CRC risk (HR: 0.25; 95% CI: 0.17, 0.36).
Conclusions: The ELD-I could reduce 13% of CRC risk, especially in individuals with a moderate genetic risk. Individuals with high ELD-I and low PRS had the lowest CRC risk than those with low ELD-I and high PRS. These findings underscore the potential role of EAT-Lancet Diet in CRC prevention.
Background: In preterm infants, the timing of human milk fortification when maternal or donor milk is offered at volumes of 60-80 mL/kg/d within the first 36 h after birth remains a matter of debate.
Objectives: This trial assessed the impact of early human milk fortification (<7 d postnatal age) on fat-free mass (FFM) z-scores.
Methods: This was an unmasked clinical trial involving preterm infants with birthweight <1800 g and gestational ages ranging from 29 0/7 to 33 6/7 weeks of gestation. Human milk-fed infants receiving feeding volumes of 60-80 mL/kg/d within the first 36 h after birth were randomly assigned to receive either early (between days 4 and 7) or delayed (between days 10 and 14) fortification using a bovine-derived fortifier. FFM was assessed at postnatal day 21 using air-displacement plethysmography.
Results: A total of 80 infants were randomly assigned. The mean birthweight was 1488 g (SD: 233). Baseline characteristics did not differ between groups. Of 80 infants randomly assigned shortly after birth, 74 had the primary outcome measured at ∼35 wk of postmenstrual age (interquartile range: 34-36). No statistically significant differences in FFM z-scores were observed between the 2 groups (-1.7 ± 0.9 compared with -1.8 ± 0.9; P = 0.64), but the early fortification group had higher weight [median difference: +131 g; 95% confidence interval (CI): 12, 236; P = 0.03], higher FFM (median difference: +103 g; 95% CI: 1, 193; P = 0.03), and higher length (mean difference: +0.9 cm; 95% CI: 0.1, 1.8; P = 0.04) at the time of body composition assessment.
Conclusions: In very preterm infants receiving early full enteral nutrition, providing early human milk fortification does not result in higher than usual FFM z-scores. This feeding strategy may, however, lead to a sustained increase in length, and transient increases in weight and FFM in grams. This study was registered at clinicaltrials.gov as NCT05525585.