Hypertension (HTN) is a well-established risk factor for cardiovascular diseases (CVDs), including ischemic heart disease, stroke, heart failure, and atrial fibrillation. The prevalence of HTN, as well as mortality rates attributable to HTN, continue to increase, particularly in the United States and among Black populations. The risk of HTN involves a complex interaction of genetics and modifiable risk factors, including dietary patterns. In this regard, there is accumulating evidence that links dietary intake of red meat with a higher risk of poorly controlled blood pressure and HTN. However, research on this topic contains significant methodological limitations, which are described in the review. The report provided below also summarizes the available research reports, with an emphasis on processed red meat consumption and how different dietary patterns among certain populations may contribute to HTN-related health disparities. Finally, this review outlines potential mechanisms and provides recommendations for providers to counsel patients with evidence-based nutritional approaches regarding red meat and the risk of HTN, as well as CVD morbidity and mortality.

Skeletal muscle quantity and quality decrease with older age, which is partly attributed to ectopic fat infiltration and has negative metabolic consequences. To inform efforts to preserve skeletal muscle with aging, a better understanding of biologic correlates of quantity and quality of muscle and intermuscular adipose tissue (IMAT) is needed. We used targeted lipidomics of lipoprotein subfractions among 947 Multi-Ethnic Study of Atherosclerosis participants to provide a detailed metabolic characterization of area and density of abdominal muscle and IMAT. Serum lipoprotein subfractions were measured at the first visit using 1H-Nuclear Magnetic Resonance spectroscopy. Muscle and IMAT area (cm²) and density (Hounsfield units) were estimated at visit 2 or 3 using computed tomography of the total abdominal, locomotion (psoas), and stabilization (paraspinal, oblique, rectus abdominis) muscles. We identified lipoprotein subfractions associated with body composition using linear regression adjusting for demographics, lifestyle, and multiple comparisons. Among 105 lipoprotein subfractions, 24 were associated with total muscle area (absolute standardized regression coefficient range: 0.07-0.10, p-values ≤ 0.002), whereas none were associated with total muscle density. When examining muscle subgroups, 25 lipoprotein subfractions were associated with stabilization muscle area, with associations strongest among the obliques. For total IMAT area, there were 27 significant associations with lipoprotein subfractions (absolute standardized regression coefficient range: 0.09-0.13, p-values ≤ 0.002). Specifically, 27 lipoprotein subfractions were associated with stabilization IMAT area, with associations strongest among the oblique and rectus abdominis muscles. For total IMAT density, there were 39 significant associations with lipoprotein subfractions (absolute standardized regression coefficient range: 0.10-0.19, p-values ≤ 0.003). Specifically, 28 and 33 lipoprotein subfractions were associated with IMAT density of locomotion and stabilization (statistically driven by obliques) muscles, respectively. Higher VLDL (cholesterol, unesterified cholesterol, phospholipids, triglycerides, and apolipoprotein B) and lower HDL (cholesterol and unesterified cholesterol) were associated with higher muscle area, higher IMAT area, and lower IMAT density. Several associations between lipoprotein subfractions and abdominal muscle area and IMAT area and density were strongest among the stabilization muscles, particularly the obliques, illustrating the importance of examining muscle groups separately. Future work is needed to determine whether the observed associations indicate a lipoprotein profile contributing to worse skeletal muscle with fat infiltration.

Purpose

Risk factors for obesity and weight gain are typically evaluated individually while "adjusting for" the influence of other confounding factors, and few studies, if any, have created risk profiles by clustering risk factors. We identified subgroups of postmenopausal women homogeneous in their clustered modifiable and non-modifiable risk factors for gaining ≥ 3% weight.

Methods

This study included 612 postmenopausal women 50-79 years old, enrolled in an ancillary study of the Women's Health Initiative Observational Study between February 1995 and July 1998. Classification and regression tree and stepwise regression models were built and compared.

Results

Of 27 selected variables, the factors significantly related to ≥ 3% weight gain were weight change in the past 2 years, age at menopause, dietary fiber, fat, alcohol intake, and smoking. In women younger than 65 years, less than 4 kg weight change in the past 2 years sufficiently reduced risk of ≥ 3% weight gain. Different combinations of risk factors related to weight gain were reported for subgroups of women: women 65 years or older (essential factor: < 9.8 g/day dietary factor), African Americans (essential factor: currently smoking), and white women (essential factor: ≥ 5 kg weight change for the past 2 years).

Conclusions

Our findings suggest specific characteristics for particular subgroups of postmenopausal women that may be useful for identifying those at risk for weight gain. The study results may be useful for targeting efforts to promote strategies to reduce the risk of obesity and weight gain in subgroups of postmenopausal women and maximize the effect of weight control by decreasing obesity-relevant adverse health outcomes.

Insulin resistance and insufficient insulin secretion are well-recognized contributors to type 2 diabetes. A potential role of reduced insulin clearance has been suggested, but few studies have investigated the contribution of insulin clearance while simultaneously examining decreased insulin sensitivity and secretion. The goal of this study was to conduct such an investigation in a cohort of 353 non-Hispanic White and African American individuals recruited in the Microbiome and Insulin Longitudinal Evaluation Study (MILES). Participants underwent oral glucose tolerance tests from which insulin sensitivity, insulin secretion, insulin clearance, and disposition index were calculated. Regression models examined the individual and joint contributions of these traits to early dysglycemia (prediabetes or newly diagnosed diabetes). In separate models, reduced insulin sensitivity, reduced disposition index, and reduced insulin clearance were associated with dysglycemia. In a joint model, only insulin resistance and reduced insulin secretion were associated with dysglycemia. Models with insulin sensitivity, disposition index, or three insulin traits had the highest discriminative value for dysglycemia (area under the receiver operating characteristics curve of 0.82 to 0.89). These results suggest that in the race groups studied, insulin resistance and compromised insulin secretion are the main independent underlying defects leading to early dysglycemia.

Background and aims

The DASH diet conveys protection against type 2 diabetes mellitus (T2D) Via plant-based and non-plant-based recommendations. Research has not identified which glucose homeostasis pathways are improved. We examined associations between adherence to a DASH diet and six glucose homeostasis traits, probing whether associations could be attributed to the plant-based (DASH-P) and/or non-plant based (DASH-NP) components.

Methods and results

We included data from 295 adults without T2D (age 59.3 ± 9.00 years; 63.46% non-Hispanic White and 36.54% African American, self-reported race ancestry) participating in the Microbiome and Insulin Longitudinal Evaluation Study (MILES). An oral glucose tolerance test (OGTT) yielded fasting plasma glucose, insulin, C-peptide, and insulin secretion, sensitivity, and disposition index. Habitual dietary intake was assessed by food frequency questionnaire (FFQ). Associations between DASH components and glucose homeostasis traits were examined, controlling for demographics, body mass index (BMI), physical activity, and energy intake. For significant associations, the models were repeated with scores for DASH-P and DASH-NP as predictors in the same model. DASH and DASH-P scores were inversely associated with fasting plasma glucose (DASH:β = -0.036 ± 0.012,P = 0.005; DASH-P: β = -0.04 ± 0.017,P = 0.002), and positively associated with insulin sensitivity (DASH:β = 0.022 ± 0.012,P = 0.042; DASH-P: = 0.036 ± 0.015,P = 0.014). The DASH score was also associated with disposition index (β = 0.026 ± 0.013,P = 0.038), but this association did not reach significance with DASH-P (β = 0.035 ± 0.018,P = 0.051). No associations were observed with DASH-NP score (all P > 0.05).

Conclusions

DASH diet is associated with improvement in specific glucose homeostasis traits, likely arising from increased plant-based foods. Such research may help tailor future dietary advice to specific metabolic risk, and to food groups most effective at improving these.

Background

Atherosclerosis and its clinical sequelae represent the leading cause of mortality among patients with nonalcoholic fatty liver disease (NAFLD). While epidemiologic data support the hepatoprotective benefits of coffee in NAFLD, whether coffee improves NAFLD-associated CVD risk is unknown.

Methods

We examined 3710 ethnically-diverse participants from the Multi-Ethnic Study of Atherosclerosis (MESA) cohort, without history of known liver disease, and with available coffee data from a validated 120-item food frequency questionnaire. All participants underwent baseline non-contrast cardiac CT from which NAFLD was defined by liver:spleen ratio (L:S<1.0), and subclinical CVD was defined by coronary artery calcium (CAC)>0. Major CVD events were defined by the first occurrence of myocardial infarction, cardiac arrest, angina, stroke, or CVD death. We used log-binomial regression to calculate the adjusted prevalence ratio (PR) for CAC>0 by coffee intake and NAFLD status, and events were compared between groups using frequency of events within adjusted Cox proportional hazard regression models.

Results

Seventeen percent (N=637) of participants met criteria for NAFLD. NAFLD participants were more likely to have elevated BMI (mean 31.1±5.5kg/m² vs. 28.0±5.2kg/m², p<0.0001), and diabetes (22% vs. 11%, p<0.0001), but did not differ in daily coffee consumption (p=0.97). Among NAFLD participants, coffee consumption was not associated with prevalent, baseline CAC>0 (PR=1.02 [0.98-1.07]). Over 12.8years of follow-up, 93 NAFLD and 415 non-NAFLD participants experienced a CV event. However, coffee intake was not associated with incident CVD events, in either NAFLD (HR=1.05 [0.91-1.21]) or non-NAFLD participants (HR=1.03 [0.97-1.11]).

Conclusion

In a large, population-based cohort, coffee consumption was not associated with the prevalence of subclinical CVD, nor did coffee impact the future risk of major CVD events, regardless of underlying NAFLD status.

Background

Poor diet quality is a risk factor for type 2 diabetes and cardiovascular disease. However, knowledge of metabolites marking adherence to Dietary Guidelines for Americans (2015 version) are limited.

Objectives

The goal was to determine a pattern of metabolites associated with the Healthy Eating Index (HEI)-2015, which measures adherence to the Dietary Guidelines for Americans.

Methods

The analysis examined 3557 adult men and women from the longitudinal cohort Multiethnic Study of Atherosclerosis (MESA), without known cardiovascular disease and with complete dietary data. Fasting serum specimens and diet and demographic questionnaires were assessed at baseline. Untargeted ¹H 1-dimensional nuclei magnetic resonance spectroscopy (600 MHz) was used to generate metabolomics and lipidomics. A metabolome-wide association study specified each spectral feature as outcomes, HEI-2015 score as predictor, adjusting for age, sex, race, and study site in linear regression analyses. Subsequently, hierarchical clustering defined the discrete groups of correlated nuclei magnetic resonance features associated with named metabolites, and the linear regression analysis assessed for associations with HEI-2015 total and component scores.

Results

The sample included 50% women with an mean age of 63 years, with 40% identifying as White, 23% as Black, 24% as Hispanic, and 13% as Chinese American. The mean HEI-2015 score was 66. The metabolome-wide association study identified 179 spectral features significantly associated with HEI-2015 score. The cluster analysis identified 7 clusters representing 4 metabolites; HEI-2015 score was significantly associated with all. HEI-2015 score was associated with proline betaine [β = 0.12 (SE = 0.02); P = 4.70 × 10^-13] and was inversely related to proline [β = -0.13 (SE = 0.02); P = 4.45 × 10^-14], 1,5 anhydrosorbitol [β = -0.08 (SE = 0.02); P = 4.37 × 10^-7] and unsaturated fatty acyl chains [β = 0.08 (SE = 0.02); P = 8.98 × 10^-7]. Intake of total fruit, whole grains, and seafood and plant proteins was associated with proline betaine.

Conclusions

Diet quality is significantly associated with unsaturated fatty acyl chains, proline betaine, and proline. Further analysis may clarify the link between diet quality, metabolites, and pathogenesis of cardiometabolic disease.

Background

Avocado consumption is linked to better glucose homeostasis, but small associations suggest potential population heterogeneity. Metabolomic data capture the effects of food intake after digestion and metabolism, thus accounting for individual differences in these processes.

Objectives

To identify metabolomic biomarkers of avocado intake and to examine their associations with glycemia.

Methods

Baseline data from 6224 multi-ethnic older adults (62% female) included self-reported avocado intake, fasting glucose and insulin, and untargeted plasma proton nuclear magnetic resonance metabolomic features (metabolomic data were available for a randomly selected subset; N = 3438). Subsequently, incident type 2 diabetes (T2D) was assessed over an ∼18 y follow-up period. A metabolome-wide association study of avocado consumption status (consumer compared with nonconsumer) was conducted, and the relationship of these features with glycemia via cross-sectional associations with fasting insulin and glucose and longitudinal associations with incident T2D was examined.

Results

Three highly-correlated spectral features were associated with avocado intake at metabolome-wide significance levels (P < 5.3 ∗ 10^-7) and combined into a single biomarker. We did not find evidence that these features were additionally associated with overall dietary quality, nor with any of 47 other food groups (all P > 0.001), supporting their suitability as a biomarker of avocado intake. Avocado intake showed a modest association only with lower fasting insulin (β = -0.07 ^+/- 0.03, P = 0.03), an association that was attenuated to nonsignificance when additionally controlling for body mass index (kg/m²). However, our biomarker of avocado intake was strongly associated with lower fasting glucose (β = -0.22 ^+/- 0.02, P < 2.0 ∗ 10^-16), lower fasting insulin (β = -0.17 ^+/- 0.02, P < 2.0 ∗ 10^-16), and a lower incidence of T2D (hazard ratio: 0.68; 0.63-074, P < 2.0 ∗ 10^-16), even when adjusting for BMI.

Conclusions

Highly significant associations between glycemia and avocado-related metabolomic features, which serve as biomarkers of the physiological impact of dietary intake after digestion and absorption, compared to modest relationships between glycemia and avocado consumption, highlights the importance of considering individual differences in metabolism when considering diet-health relationships.

Background

Whether red meat consumption is associated with higher inflammation or confounded by increased adiposity remains unclear. Plasma metabolites capture the effects of diet after food is processed, digested, and absorbed, and correlate with markers of inflammation, so they can help clarify diet-health relationships.

Objective

To identify whether any metabolites associated with red meat intake are also associated with inflammation.

Methods

A cross-sectional analysis of observational data from older adults (52.84% women, mean age 63 ± 0.3 y) participating in the Multi-Ethnic Study of Atherosclerosis (MESA). Dietary intake was assessed by food-frequency questionnaire, alongside C-reactive protein (CRP), interleukin-2, interleukin-6, fibrinogen, homocysteine, and tumor necrosis factor alpha, and untargeted proton nuclear magnetic resonance (¹H NMR) metabolomic features. Associations between these variables were examined using linear regression models, adjusted for demographic factors, lifestyle behaviors, and body mass index (BMI).

Results

In analyses that adjust for BMI, neither processed nor unprocessed forms of red meat were associated with any markers of inflammation (all P > 0.01). However, when adjusting for BMI, unprocessed red meat was inversely associated with spectral features representing the metabolite glutamine (sentinel hit: β = -0.09 ± 0.02, P = 2.0 × 10^-5), an amino acid which was also inversely associated with CRP level (β = -0.11 ± 0.01, P = 3.3 × 10^-10).

Conclusions

Our analyses were unable to support a relationship between either processed or unprocessed red meat and inflammation, over and above any confounding by BMI. Glutamine, a plasma correlate of lower unprocessed red meat intake, was associated with lower CRP levels. The differences in diet-inflammation associations, compared with diet metabolite-inflammation associations, warrant further investigation to understand the extent that these arise from the following: 1) a reduction in measurement error with metabolite measures; 2) the extent that which factors other than unprocessed red meat intake contribute to glutamine levels; and 3) the ability of plasma metabolites to capture individual differences in how food intake is metabolized.

Background and aims

To investigate associations between avocado intake and glycemia in adults with Hispanic/Latino ancestry.

Methods and results

The associations of avocado intake with measures of insulin and glucose homeostasis were evaluated in a cross-sectional analysis of up to 14,591 Hispanic/Latino adults, using measures of: average glucose levels (hemoglobin A1c; HbA1c), fasting glucose and insulin, glucose and insulin levels after an oral glucose tolerance test (OGTT), and calculated measures of insulin resistance (HOMA-IR, and HOMA-%β), and insulinogenic index. Associations were assessed using multivariable linear regression models, which controlled for sociodemographic factors and health behaviors, and which were stratified by dysglycemia status. In those with normoglycemia, avocado intake was associated with a higher insulinogenic index (β = 0.17 ± 0.07, P = 0.02). In those with T2D (treated and untreated), avocado intake was associated with lower hemoglobin A1c (HbA1c; β = -0.36 ± 0.21, P = 0.02), and lower fasting glucose (β = -0.27 ± 0.12, P = 0.02). In the those with untreated T2D, avocado intake was additionally associated with HOMA-%β (β = 0.39 ± 0.19, P = 0.04), higher insulin values 2-h after an oral glucose load (β = 0.62 ± 0.23, P = 0.01), and a higher insulinogenic index (β = 0.42 ± 0.18, P = 0.02). No associations were observed in participants with prediabetes.

Conclusions

We observed an association of avocado intake with better glucose/insulin homeostasis, especially in those with T2D.