Variations in Dietary Patterns Defined by the Healthy Eating Index 2015 and Associations with Mortality: Findings from the Dietary Patterns Methods Project

BACKGROUND

It is currently unknown if within high-quality dietary intake there exist distinct dietary patterns associated with health benefits that are identifiable with multidimensional dietary pattern analyses. The purpose of this study was to identify specific dietary patterns and groups therein and their associations with all-cause, CVD, and cancer mortality.

METHODS

We conducted sex-specific k-means cluster analyses within Healthy Eating Index 2015 (HEI-2015) quintile 5 in 3 US cohorts [NIH-American Association of Retired Persons Diet and Health Study (AARP), the Multiethnic Cohort (MEC), Women's Health Initiative Observational Study (WHI OS)], clusters ranging from n = 1190 to n = 12,007. Characterizations incorporated HEI-2015 overall and component-specific percentage adherence goals, using untruncated and truncated radar graphs and shape analyses. Using cohort- and sex-specific Cox proportional hazards models, associations of quintile 5 clusters with all-cause, cardiovascular disease (CVD), and cancer mortality were evaluated relative to quintile 1.

RESULTS

In each cohort sex-specific sample, 3 identified clusters included 16%-62% of participants, providing evidence for variation within high-quality dietary intake. Clusters revealed commonalities in total fruits and whole fruits intakes that exceeded goals and high sodium intake. Dairy and whole grain intakes oftentimes fell below goal. Some clusters were in addition characterized by total vegetables, greens & beans, and seafood & plant protein intakes exceeding goals. All high-quality dietary patterns were associated with a multivariable-adjusted significant 15%-26% lower risk of all-cause death than diet intake in quintile 1 (except for cluster 2 in WHI OS), and with a 16%-25% lower risk of CVD mortality in the AARP and MEC cohorts. Cancer mortality results were inconsistent.

CONCLUSIONS

Multiple ways to achieve a high-quality diet were identified and significant associations with lower all-cause and CVD mortality were seen in some cohorts.

Associations of circulating choline and its related metabolites with cardiometabolic biomarkers: an international pooled analysis

BACKGROUND

Choline is an essential nutrient; however, the associations of choline and its related metabolites with cardiometabolic risk remain unclear.

OBJECTIVE

We examined the associations of circulating choline, betaine, carnitine, and dimethylglycine (DMG) with cardiometabolic biomarkers and their potential dietary and nondietary determinants.

METHODS

The cross-sectional analyses included 32,853 participants from 17 studies, who were free of cancer, cardiovascular diseases, chronic kidney diseases, and inflammatory bowel disease. In each study, metabolites and biomarkers were log-transformed and standardized by means and SDs, and linear regression coefficients (β) and 95% CIs were estimated with adjustments for potential confounders. Study-specific results were combined by random-effects meta-analyses. A false discovery rate <0.05 was considered significant.

RESULTS

We observed moderate positive associations of circulating choline, carnitine, and DMG with creatinine [β (95% CI): 0.136 (0.084, 0.188), 0.106 (0.045, 0.168), and 0.128 (0.087, 0.169), respectively, for each SD increase in biomarkers on the log scale], carnitine with triglycerides (β = 0.076; 95% CI: 0.042, 0.109), homocysteine (β = 0.064; 95% CI: 0.033, 0.095), and LDL cholesterol (β = 0.055; 95% CI: 0.013, 0.096), DMG with homocysteine (β = 0.068; 95% CI: 0.023, 0.114), insulin (β = 0.068; 95% CI: 0.043, 0.093), and IL-6 (β = 0.060; 95% CI: 0.027, 0.094), but moderate inverse associations of betaine with triglycerides (β = -0.146; 95% CI: -0.188, -0.104), insulin (β = -0.106; 95% CI: -0.130, -0.082), homocysteine (β = -0.097; 95% CI: -0.149, -0.045), and total cholesterol (β = -0.074; 95% CI: -0.102, -0.047). In the whole pooled population, no dietary factor was associated with circulating choline; red meat intake was associated with circulating carnitine [β = 0.092 (0.042, 0.142) for a 1 serving/d increase], whereas plant protein was associated with circulating betaine [β = 0.249 (0.110, 0.388) for a 5% energy increase]. Demographics, lifestyle, and metabolic disease history showed differential associations with these metabolites.

CONCLUSIONS

Circulating choline, carnitine, and DMG were associated with unfavorable cardiometabolic risk profiles, whereas circulating betaine was associated with a favorable cardiometabolic risk profile. Future prospective studies are needed to examine the associations of these metabolites with incident cardiovascular events.

Circulating trimethylamine N-oxide in association with diet and cardiometabolic biomarkers: an international pooled analysis

BACKGROUND

Trimethylamine N-oxide (TMAO), a diet-derived, gut microbial-host cometabolite, has been linked to cardiometabolic diseases. However, the relations remain unclear between diet, TMAO, and cardiometabolic health in general populations from different regions and ethnicities.

OBJECTIVES

To examine associations of circulating TMAO with dietary and cardiometabolic factors in a pooled analysis of 16 population-based studies from the United States, Europe, and Asia.

METHODS

Included were 32,166 adults (16,269 white, 13,293 Asian, 1247 Hispanic/Latino, 1236 black, and 121 others) without cardiovascular disease, cancer, chronic kidney disease, or inflammatory bowel disease. Linear regression coefficients (β) were computed for standardized TMAO with harmonized variables. Study-specific results were combined by random-effects meta-analysis. A false discovery rate <0.10 was considered significant.

RESULTS

After adjustment for potential confounders, circulating TMAO was associated with intakes of animal protein and saturated fat (β = 0.124 and 0.058, respectively, for a 5% energy increase) and with shellfish, total fish, eggs, and red meat (β = 0.370, 0.151, 0.081, and 0.056, respectively, for a 1 serving/d increase). Plant protein and nuts showed inverse associations (β = -0.126 for a 5% energy increase from plant protein and -0.123 for a 1 serving/d increase of nuts). Although the animal protein-TMAO association was consistent across populations, fish and shellfish associations were stronger in Asians (β = 0.285 and 0.578), and egg and red meat associations were more prominent in Americans (β = 0.153 and 0.093). Besides, circulating TMAO was positively associated with creatinine (β = 0.131 SD increase in log-TMAO), homocysteine (β = 0.065), insulin (β = 0.048), glycated hemoglobin (β = 0.048), and glucose (β = 0.023), whereas it was inversely associated with HDL cholesterol (β = -0.047) and blood pressure (β = -0.030). Each TMAO-biomarker association remained significant after further adjusting for creatinine and was robust in subgroup/sensitivity analyses.

CONCLUSIONS

In an international, consortium-based study, animal protein was consistently associated with increased circulating TMAO, whereas TMAO associations with fish, shellfish, eggs, and red meat varied among populations. The adverse associations of TMAO with certain cardiometabolic biomarkers, independent of renal function, warrant further investigation.

Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts

BACKGROUND

Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction.

METHODS

We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.

RESULTS

Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail.

CONCLUSIONS

Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.