Psyllium fiber effectively improves conventional and alternative lipids markers, potentially delaying the process of atherosclerosis-associated CVD risk in those with or without hypercholesterolemia. This trial is registered at www.clinicaltrials.gov as NCT03346733.

Adherence to the DASH diet is inversely associated with T2DM risk. Metabolic changes due to DASH adherence and their potential relationship with incident T2DM have not been described. The objective is to determine metabolite clusters associated with adherence to a DASH-like diet in the Insulin Resistance Atherosclerosis Study (IRAS) cohort and explore if the clusters predicted 5-year incidence of T2DM. The current study included the 570 non-diabetic multi-ethnic participants aged 40 - 69 years. Adherence to a DASH-like diet was determined a priori through an 80-point scale for absolute intakes of the eight DASH food groups. Quantitative measurements of 87 metabolites (acylcarnitines, amino acids, bile acids, sterols, and fatty acids) were obtained at baseline. Metabolite clusters related to DASH adherence were determined through partial least squares (PLS) analysis using R. Multivariable-adjusted logistic regression (MLR) was used to explore the associations between metabolite clusters and incident T2DM. A group of acylcarnitines and fatty acids loaded strongly on the two components retained under PLS. Among strongly loading metabolites, a select group of acylcarnitines had over 50% of their individual variance explained by the PLS model. Component 2 was inversely associated with incident T2DM (Odds ratio (OR): 0.89; 95% Confidence interval (CI) 0.80-0.99, p-value = 0.043) after adjustment for demographic and metabolic covariates. Component 1 was not associated with T2DM risk (OR: 1.02; 95% CI 0.88-1.19, p-value = 0.74). Adherence to a DASH-type diet may contribute to reduced T2DM risk in part through modulations in acylcarnitine and fatty acid physiology.

Background Dental care expenses are reported to present higher financial barriers than any other type of health care service in the United States. Social media platforms such as Twitter have become a source of public health communication and surveillance. Previous studies have demonstrated the usefulness of Twitter in exploring public opinion on aspects of dental care. To date, no studies have leveraged Twitter to examine public sentiments regarding dental care affordability in the United States. Objective The aim of this study is to understand public perceptions of dental care affordability in the United States on the social media site, Twitter. Methods Tweets posted between September 1, 2017, and September 30, 2021, were collected using the Snscrape application. Query terms were selected a priori to represent dentistry and financial aspects associated with dental treatment. Data were analyzed qualitatively using both deductive and inductive approaches. In total, 8% (440/5500) of all included tweets were coded to identify prominent themes and subthemes. The entire sample of included tweets were then independently coded into thematic categories. Quantitative data analyses included geographic distribution of tweets by state, volume analysis of tweets over time, and distribution of tweets by content theme. Results A final sample of 5314 tweets were included in the study. Thematic analysis identified the following prominent themes: (1) general sentiments (1614 tweets, 30.4%); (2) delaying or forgoing dental care (1190 tweets, 22.4%); (3) payment strategies (1019 tweets, 19.2%); (4) insurance (767 tweets, 14.4%); and (5) policy statements (724 tweets, 13.6%). Geographic distributions of the tweets established California, Texas, Florida, and New York as the states with the most tweets. Qualitative analysis revealed barriers faced by individuals to accessing dental care, strategies taken to cope with dental pain, and public perceptions on aspects of dental care policy. The volume and thematic trends of the tweets corresponded to relevant societal events, including the COVID-19 pandemic and debates on health care policy resulting from the election of President Joseph R. Biden. Conclusions The findings illustrate the real-time sentiment of social media users toward the cost of dental treatment and suggest shortcomings in funding that may be representative of greater systemic failures in the provision of dental care. Thus, this study provides insights for policy makers and dental professionals who strive to increase access to dental care.

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Background: The DASH diet is inversely associated with T2DM risk. Metabolic changes due to DASH adherence and their potential relationship with incident T2DM have not been described. Objective: To determine metabolite clusters associated with adherence to a DASH-type diet in the Insulin Resistance Atherosclerosis Study (IRAS) cohort and explore if they predict 5-year T2DM incidence. Methods: DASH adherence for 570 nondiabetic multi-ethnic participants aged 40-69 years was determined using a 10-point scale for 8 DASH food groups. Data for 88 metabolites (acylcarnitines, amino acids, bile acids, sterols, and fatty acids) were obtained at baseline. Metabolite clusters associated with a DASH-type diet were determined using partial least squares analysis (PLS). Multivariable-adjusted logistic regression was used to explore the associations between metabolite clusters and incident T2DM. Results: A group of acylcarnitines loaded strongly on two components retained under PLS (Figure). Component 2 was inversely associated with incident T2DM (OR: 0.86; 95% CI 0.79-0.95) after adjustment for demographic and metabolic covariates. Component 1 was not associated with T2DM risk (OR: 0.97; 95% CI 0.87-1.10). Conclusion: Adherence to a DASH-type diet may contribute to reduced T2DM risk in part through modulations in acylcarnitine physiology. Disclosure S. Yashpal: None. A.D. Liese: None. L.E. Wagenknecht: None. S.M. Haffner: None. L.W. Johnston: None. B. Boucher: None. R.P. Bazinet: None. M. Rewers: None. J.I. Rotter: None. S.M. Watkins: Stock/Shareholder; Self; Verso Biosciences, Inc. A. Hanley: None. Funding National Institutes of Health