A Healthy Beverage Score and Risk of Chronic Kidney Disease Progression, Incident Cardiovascular Disease, and All-Cause Mortality in the Chronic Renal Insufficiency Cohort

The Beverage Quality Index and risk of cardiometabolic outcomes after a myocardial infarction: A prospective analysis in the Alpha Omega Cohort

BACKGROUND AND AIMS

Individual beverages have varying associations with cardiometabolic outcomes, but little is known about overall beverage quality and cardiometabolic risk after myocardial infarction (MI). We created the Beverage Quality Index (BQI) to assess beverage quality and examined its association with cardiometabolic outcomes after MI.

METHODS AND RESULTS

We included 4365 Dutch post-MI patients from the Alpha Omega Cohort, aged 60-80 years. Diet was assessed at baseline (2002-2006) with a 203-item FFQ. The BQI included eight components (coffee, tea, milk, juices, sugar-sweetened beverages, alcohol, added sugar to coffee and tea, and energy from beverages), and ranged from 0 to 80. Multivariable Cox models were used to estimate HRs for the BQI in relation to incident diabetes mellitus (DM), major adverse cardiovascular events (MACE), recurrent cardiovascular disease (CVD) and fatal CVD over 3.4 y of follow-up, with follow-up for fatal CVD extended through 2018 (12.4 y). The average BQI was 50.0 ± 12.5. During 3.4 y of follow-up, we identified 186 incident cases of DM, 601 of MACE, 310 of recurrent CVD and 140 of fatal CVD. In multivariable models, a higher BQI (T3 vs. T1) was associated with lower risk of MACE [HR: 0.73 (0.59-0.90)], and recurrent CVD [HR: 0.67 (0.50-0.91)], but not with DM or CVD mortality. After 12.4 y of follow-up, 903 CVD deaths occurred. A significant inverse association with CVD mortality during long-term follow-up was found [HR: 0.81 (0.68-0.96)].

CONCLUSION

Overall beverage intake quality, as assessed by the BQI, may represent an important target for the prevention of recurrent CVD.

The healthy beverage index is not associated with insulin resistance, prediabetes and type 2 diabetes risk in the Rotterdam Study

PURPOSE

Whether beverage quality affects changes in glycaemic traits and type 2 diabetes (T2D) risk is unknown. We examined associations of a previously developed Healthy Beverage Index (HBI) with insulin resistance, and risk of prediabetes and T2D.

METHODS

We included 6769 participants (59% female, 62.0 ± 7.8 years) from the Rotterdam Study cohort free of diabetes at baseline. Diet was assessed using food-frequency questionnaires at baseline. The HBI included 10 components (energy from beverages, meeting fluid requirements, water, coffee and tea, low-fat milk, diet drinks, juices, alcohol, full-fat milk, and sugar-sweetened beverages), with a total score ranging from 0 to 100. A higher score represents a healthier beverage pattern. Data on study outcomes were available from 1993 to 2015. Multivariable linear mixed models and Cox proportional-hazards regression models were used to examine associations of the HBI (per 10 points increment) with two measurements of HOMA-IR (a proxy for insulin resistance), and risk of prediabetes and T2D.

RESULTS

During follow-up, we documented 1139 prediabetes and 784 T2D cases. Mean ± SD of the HBI was 66.8 ± 14.4. Higher HBI score was not associated with HOMA-IR (β: 0.003; 95% CI - 0.007, 0.014), or with risk of prediabetes (HR: 1.01; 95% CI 0.97, 1.06), or T2D (HR: 1.01; 95% CI 0.96, 1.07).

CONCLUSION

Our findings suggest no major role for overall beverage intake quality assessed with the HBI in insulin resistance, prediabetes and T2D incidence. The HBI may not be an adequate tool to assess beverage intake quality in our population.

Healthy beverages may reduce the genetic risk of abdominal obesity and related metabolic comorbidities: a gene-diet interaction study in Iranian women

BACKGROUND & AIMS

The nutrition transition in developing countries like Iran causes the increasing rise of obesity and abdominal obesity rates. However, it is not yet well proven that environmental modifications like improving the quality of beverage intake can be effective in people who have a genetic predisposition to obesity. So, in the present study, we examine the interaction between genetic predisposition and healthy beverage index (HBI) with abdominal obesity and obesity-related metabolic risk factors in overweight and obese women.

METHOD

Based on inclusion and exclusion criteria, 202 overweight or obese females were chosen for this cross-sectional study. Body composition, anthropometric measures, physical activity, and beverage intake data were collected and analyzed using recognized and trustworthy methodologies. Biochemical tests were performed on serum samples. A genetic risk score (GRS) was calculated based on the results of genetic tests. The predetermined HBI was calculated based on previous studies. A generalized linear model was used to estimate the interactions between GRS and HBI (GLM).

RESULTS

We found significant interactions between GRS and HBI on WHR (β = - 0.39, CI: -0.07 to 0.001, P = 0.05) and WC (β = - 6.18, CI: - 13.41 to 1.05, P = 0.09). Also, there were significant gene-diet interactions for HBI and GRS on HDL (β = 7.09, CI: - 0.73 to 14.92, P = 0.07) and FBS (β = - 9.07, CI: - 18.63 to 0.47, P = 0.06).

CONCLUSIONS

These findings emphasize the HBI considering genetics appears to protect against the risks of abdominal obesity and metabolic associated obesity markers.

Adherence to a Healthy Beverage Score Is Associated with Lower Frailty Risk in Older Adults

Many beverages include bioactive components and energy but are frequently not considered in diet quality estimations. We examined the association of a healthy beverage score (HBS) with incident frailty in older adults from the Seniors-ENRICA-1 cohort. We used data from 1900 participants (mean ± SD age 68.7 ± 6.4 years, 51.7% women), recruited in 2008–2010 and followed-up until 2012 assessing food consumption at baseline with a validated diet history. The HBS was higher for increasing consumption of low fat milk, tea/coffee, lower consumption of whole milk, fruit juice, artificially sweetened beverages, sugar-sweetened beverages, and moderate intake of alcohol. Frailty was considered as having ≥3 criteria: exhaustion, low-physical activity, slow gait speed, weakness, and weight loss. We performed logistic regression analyses adjusted for potential confounders. During a 3.5 y mean follow-up, 136 new cases of frailty occurred. Compared to the lowest sex-specific HBS tertile, the fully adjusted odds ratio (95% confidence interval) of frailty was 0.59 (0.38, 0.92) in the intermediate tertile, and 0.52 (0.31, 0.88) in the highest tertile, p trend = 0.007. Results for slow gait speed were 0.79 (0.58, 1.07) and 0.71 (0.51–0.99), p trend = 0.033. Therefore, adherence to HBS was inversely associated with incident frailty and slow gait speed. HBS can help on the beverage quality evaluation, highlighting beverage importance as contributors to diet and to health.

Metabolites Associated with Coffee Consumption and Incident Chronic Kidney Disease

BACKGROUND AND OBJECTIVES

Moderate coffee consumption has been associated with lower risk of CKD; however, the exact biologic mechanisms underlying this association are unknown. Metabolomic profiling may identify metabolic pathways that explain the association between coffee and CKD. The goal of this study was to identify serum metabolites associated with coffee consumption and examine the association between these coffee-associated metabolites and incident CKD.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Using multivariable linear regression, we identified coffee-associated metabolites among 372 serum metabolites available in two subsamples of the Atherosclerosis Risk in Communities study (ARIC; n=3811). Fixed effects meta-analysis was used to pool the results from the two ARIC study subsamples. Associations between coffee and metabolites were replicated in the Bogalusa Heart Study (n=1043). Metabolites with significant associations with coffee in both cohorts were then evaluated for their prospective associations with incident CKD in the ARIC study using Cox proportional hazards regression.

RESULTS

In the ARIC study, mean (SD) age was 54 (6) years, 56% were daily coffee drinkers, and 32% drank >2 cups per day. In the Bogalusa Heart Study, mean (SD) age was 48 (5) years, 57% were daily coffee drinkers, and 38% drank >2 cups per day. In a meta-analysis of two subsamples of the ARIC study, 41 metabolites were associated with coffee consumption, of which 20 metabolites replicated in the Bogalusa Heart Study. Three of these 20 coffee-associated metabolites were associated with incident CKD in the ARIC study.

CONCLUSIONS

We detected 20 unique serum metabolites associated with coffee consumption in both the ARIC study and the Bogalusa Heart Study, and three of these 20 candidate biomarkers of coffee consumption were associated with incident CKD. One metabolite (glycochenodeoxycholate), a lipid involved in primary bile acid metabolism, may contribute to the favorable kidney health outcomes associated with coffee consumption. Two metabolites (O-methylcatechol sulfate and 3-methyl catechol sulfate), both of which are xenobiotics involved in benzoate metabolism, may represent potential harmful aspects of coffee on kidney health.

Risk Factors for CKD Progression: Overview of Findings from the CRIC Study

The Chronic Renal Insufficiency Cohort (CRIC) Study is an ongoing, multicenter, longitudinal study of nearly 5500 adults with CKD in the United States. Over the past 10 years, the CRIC Study has made significant contributions to the understanding of factors associated with CKD progression. This review summarizes findings from longitudinal studies evaluating risk factors associated with CKD progression in the CRIC Study, grouped into the following six thematic categories: (1) sociodemographic and economic (sex, race/ethnicity, and nephrology care); (2) behavioral (healthy lifestyle, diet, and sleep); (3) genetic (apoL1, genome-wide association study, and renin-angiotensin-aldosterone system pathway genes); (4) cardiovascular (atrial fibrillation, hypertension, and vascular stiffness); (5) metabolic (fibroblast growth factor 23 and urinary oxalate); and (6) novel factors (AKI and biomarkers of kidney injury). Additionally, we highlight areas where future research is needed, and opportunities for interdisciplinary collaboration.