The Effect of Non-Nutritive Sweetened Beverages on Postprandial Glycemic and Endocrine Responses: A Systematic Review and Network Meta-Analysis.

Background: There has been an emerging concern that non-nutritive sweeteners (NNS) can increase the risk of cardiometabolic disease. Much of the attention has focused on acute metabolic and endocrine responses to NNS. To examine whether these mechanisms are operational under real-world scenarios, we conducted a systematic review and network meta-analysis of acute trials comparing the effects of non-nutritive sweetened beverages (NNS beverages) with water and sugar-sweetened beverages (SSBs) in humans. Methods: MEDLINE, EMBASE, and The Cochrane Library were searched through to January 15, 2022. We included acute, single-exposure, randomized, and non-randomized, clinical trials in humans, regardless of health status. Three patterns of intake were examined: (1) uncoupling interventions, where NNS beverages were consumed alone without added energy or nutrients; (2) coupling interventions, where NNS beverages were consumed together with added energy and nutrients as carbohydrates; and (3) delayed coupling interventions, where NNS beverages were consumed as a preload prior to added energy and nutrients as carbohydrates. The primary outcome was a 2 h incremental area under the curve (iAUC) for blood glucose concentration. Secondary outcomes included 2 h iAUC for insulin, glucagon-like peptide 1 (GLP-1), gastric inhibitory polypeptide (GIP), peptide YY (PYY), ghrelin, leptin, and glucagon concentrations. Network meta-analysis and confidence in the network meta-analysis (CINeMA) were conducted in R-studio and CINeMA, respectively. Results: Thirty-six trials involving 472 predominantly healthy participants were included. Trials examined a variety of single NNS (acesulfame potassium, aspartame, cyclamate, saccharin, stevia, and sucralose) and NNS blends (acesulfame potassium + aspartame, acesulfame potassium + sucralose, acesulfame potassium + aspartame + cyclamate, and acesulfame potassium + aspartame + sucralose), along with matched water/unsweetened controls and SSBs sweetened with various caloric sugars (glucose, sucrose, and fructose). In uncoupling interventions, NNS beverages (single or blends) had no effect on postprandial glucose, insulin, GLP-1, GIP, PYY, ghrelin, and glucagon responses similar to water controls (generally, low to moderate confidence), whereas SSBs sweetened with caloric sugars (glucose and sucrose) increased postprandial glucose, insulin, GLP-1, and GIP responses with no differences in postprandial ghrelin and glucagon responses (generally, low to moderate confidence). In coupling and delayed coupling interventions, NNS beverages had no postprandial glucose and endocrine effects similar to controls (generally, low to moderate confidence). Conclusions: The available evidence suggests that NNS beverages sweetened with single or blends of NNS have no acute metabolic and endocrine effects, similar to water. These findings provide support for NNS beverages as an alternative replacement strategy for SSBs in the acute postprandial setting.

Association of Low- and No-Calorie Sweetened Beverages as a Replacement for Sugar-Sweetened Beverages With Body Weight and Cardiometabolic Risk: A Systematic Review and Meta-analysis.

Importance: There are concerns that low- and no-calorie sweetened beverages (LNCSBs) do not have established benefits, with major dietary guidelines recommending the use of water and not LNCSBs to replace sugar-sweetened beverages (SSBs). Whether LNCSB as a substitute can yield similar improvements in cardiometabolic risk factors vs water in their intended substitution for SSBs is unclear. Objective: To assess the association of LNCSBs (using 3 prespecified substitutions of LNCSBs for SSBs, water for SSBs, and LNCSBs for water) with body weight and cardiometabolic risk factors in adults with and without diabetes. Data Sources: Medline, Embase, and the Cochrane Central Register of Controlled Trials were searched from inception through December 26, 2021. Study Selection: Randomized clinical trials (RCTs) with at least 2 weeks of interventions comparing LNCSBs, SSBs, and/or water were included. Data Extraction and Synthesis: Data were extracted and risk of bias was assessed by 2 independent reviewers. A network meta-analysis was performed with data expressed as mean difference (MD) or standardized mean difference (SMD) with 95% CIs. The GRADE (Grading of Recommendations Assessment, Development and Evaluation) system was used to assess the certainty of the evidence. Main Outcomes and Measures: The primary outcome was body weight. Secondary outcomes were other measures of adiposity, glycemic control, blood lipids, blood pressure, measures of nonalcoholic fatty liver disease, and uric acid. Results: A total of 17 RCTs with 24 trial comparisons were included, involving 1733 adults (mean [SD] age, 33.1 [6.6] years; 1341 women [77.4%]) with overweight or obesity who were at risk for or had diabetes. Overall, LNCSBs were a substitute for SSBs in 12 RCTs (n = 601 participants), water was a substitute for SSBs in 3 RCTs (n = 429), and LNCSBs were a substitute for water in 9 RCTs (n = 974). Substitution of LNCSBs for SSBs was associated with reduced body weight (MD, -1.06 kg; 95% CI, -1.71 to -0.41 kg), body mass index (MD, -0.32; 95% CI, -0.58 to -0.07), percentage of body fat (MD, -0.60%; 95% CI, -1.03% to -0.18%), and intrahepatocellular lipid (SMD, -0.42; 95% CI, -0.70 to -0.14). Substituting water for SSBs was not associated with any outcome. There was also no association found between substituting LNCSBs for water with any outcome except glycated hemoglobin A1c (MD, 0.21%; 95% CI, 0.02% to 0.40%) and systolic blood pressure (MD, -2.63 mm Hg; 95% CI, -4.71 to -0.55 mm Hg). The certainty of the evidence was moderate (substitution of LNCSBs for SSBs) and low (substitutions of water for SSBs and LNCSBs for water) for body weight and was generally moderate for all other outcomes across all substitutions. Conclusions and Relevance: This systematic review and meta-analysis found that using LNCSBs as an intended substitute for SSBs was associated with small improvements in body weight and cardiometabolic risk factors without evidence of harm and had a similar direction of benefit as water substitution. The evidence supports the use of LNCSBs as an alternative replacement strategy for SSBs over the moderate term in adults with overweight or obesity who are at risk for or have diabetes.

Clinically Practical Approach for Screening of Low Muscularity Using Electronic Linear Measures on Computed Tomography Images in Critically Ill Patients.

BACKGROUND: Computed tomography (CT) scans performed during routine hospital care offer the opportunity to quantify skeletal muscle and predict mortality and morbidity in intensive care unit (ICU) patients. Existing methods of muscle cross-sectional area (CSA) quantification require specialized software, training, and time commitment that may not be feasible in a clinical setting. In this article, we explore a new screening method to identify patients with low muscle mass. METHODS: We analyzed 145 scans of elderly ICU patients (≥65 years old) using a combination of measures obtained with a digital ruler, commonly found on hospital radiological software. The psoas and paraspinal muscle groups at the level of the third lumbar vertebra (L3) were evaluated by using 2 linear measures each and compared with an established method of CT image analysis of total muscle CSA in the L3 region. RESULTS: There was a strong association between linear measures of psoas and paraspinal muscle groups and total L3 muscle CSA (R2 = 0.745, P < 0.001). Linear measures, age, and sex were included as covariates in a multiple logistic regression to predict those with low muscle mass; receiver operating characteristic (ROC) area under the curve (AUC) of the combined psoas and paraspinal linear index model was 0.920. Intraclass correlation coefficients (ICCs) were used to evaluate intrarater and interrater reliability, resulting in scores of 0.979 (95% CI: 0.940-0.992) and 0.937 (95% CI: 0.828-0.978), respectively. CONCLUSIONS: A digital ruler can reliably predict L3 muscle CSA, and these linear measures may be used to identify critically ill patients with low muscularity who are at risk for worse clinical outcomes.