Association of fruit and vegetable color with incident diabetes and cardiometabolic risk biomarkers in the United States Hispanic/Latino population

High-quality fruit and vegetable characterized by cardiometabolic biomarkers and its relation to major chronic disease risk: results from 3 prospective United States cohort studies

BACKGROUND

The current guidelines recommend a specified total serving of fruits and vegetables (FV). However, how differences in their nutritional quality of specific FV influence overall health remains unclear.

OBJECTIVES

To identify high-quality FV using 14 cardiometabolic biomarkers, and assess their consumption, alongside overall FV intake, with chronic disease risk.

METHODS

We used data from 3 prospective cohorts, Health Professionals Follow-up Study, Nurses' Health Study (NHS), and NHSII. Diet was assessed at baseline and updated every 4 y. Biomarker analysis was conducted on 41,714 participants using generalized linear models. Metabolic quality was ascertained by each FV's association with biomarkers. Major chronic disease risk analysis involved 207,241 participants followed for 32 y with Cox proportional hazards models. We also analyzed atherosclerotic cardiovascular disease (ASCVD), type 2 diabetes (T2D), cancer, and chronic obstructive pulmonary disease (COPD) as secondary outcomes.

RESULTS

Of 52 FV items, 19 were identified as high-metabolic quality (top 5: apples/pears, iceberg/head lettuce, raw spinach, alfalfa sprouts, and eggplant/summer squash). In disease risk analysis, 60,712 major chronic disease events were recorded. A higher proportion of high-metabolic quality FV intake was associated with lower chronic disease risk across total FV quantity levels. In each quantity level stratum (quartiles Q1-Q4), comparing the highest to the lowest quality proportion quartiles, the hazard ratio (HR) (95% confidence interval [CI]) were 0.85 (0.81-0.90), 0.86 (0.82-0.90), 0.84 (0.80-0.89), and 0.89 (0.84-0.94), all P-trend < 0.001. Patterns were similar for ASCVD, T2D, and COPD but less consistent for cancer. High total FV intake, if consisting mostly of neutral or low-metabolic quality items, was not associated with lower chronic disease risk. For diabetes specifically, these were associated with significantly higher risk [quantity-Q3, HR: 1.13 (1.05, 1.22); quantity-Q4, HR: 1.17 (1.07, 1.28)].

CONCLUSIONS

Our findings indicate the importance of considering both quality and quantity of FV for health, and support dietary guidelines to emphasize high-metabolic quality FV consumption alongside overall intake.

Effects and mechanisms of anti-diabetic dietary natural products: an updated review

Diabetes is a global public health issue, characterized by an abnormal level of blood glucose. It can be classified into type 1, type 2, gestational, and other rare diabetes. Recent studies have reported that many dietary natural products exhibit anti-diabetic activity. In this narrative review, the effects and underlying mechanisms of dietary natural products on diabetes are summarized based on the results from epidemiological, experimental, and clinical studies. Some fruits (e.g., grape, blueberry, and cherry), vegetables (e.g., bitter melon and Lycium barbarum leaves), grains (e.g., oat, rye, and brown rice), legumes (e.g., soybean and black bean), spices (e.g., cinnamon and turmeric) and medicinal herbs (e.g., Aloe vera leaf and Nigella sativa), and vitamin C and carotenoids could play important roles in the prevention and management of diabetes. Their underlying mechanisms include exerting antioxidant, anti-inflammatory, and anti-glycation effects, inhibiting carbohydrate-hydrolyzing enzymes, enhancing insulin action, alleviating insulin resistance, modulating the gut microbiota, and so on. This review can provide people with a comprehensive knowledge of anti-diabetic dietary natural products, and support their further development into functional food to prevent and manage diabetes.

Association of pre-diagnosis specific color groups of fruit and vegetable intake with ovarian cancer survival: results from the ovarian cancer follow-up study (OOPS)

Background: The colors of fruits and vegetables (FV) reflect the presence of pigmented bioactive compounds. The evidence of pre-diagnosis specific FV color group intake contributing to ovarian cancer (OC) survival is limited and inconsistent. Methods: A prospective cohort study was conducted between 2015 and 2020 with 700 newly diagnosed OC patients. Pre-diagnosis dietary information was assessed by a validated food frequency questionnaire. We classified FV into five groups based on the color of their edible parts (e.g., green, red/purple, orange/yellow, white, and uncategorized groups). Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of specific color groups of FV before diagnosis with OC survival. Potential multiplicative and additive interactions were assessed. Results: 130 patients died during a median follow-up of 37.57 (interquartile: 24.77-50.20) months. We observed the improved survival with a higher pre-diagnosis intake of total FV (HRtertile 3 vs. tertile 1 = 0.63, 95%CI = 0.40-0.99), total vegetables (HRtertile 3 vs. tertile 1 = 0.57, 95%CI = 0.36-0.90), and red/purple FV (HRtertile 3 vs. tertile 1 = 0.52, 95%CI = 0.33-0.82). In addition, we observed significant dose-response relationships for per standard deviation increment between total vegetable intake (HR = 0.79, 95%CI = 0.65-0.96) and red/purple group intake (HR = 0.77, 95%CI = 0.60-0.99) before diagnosis with OC survival. Additionally, pre-diagnosis green FV intake was borderline associated with better OC survival (HRper standard deviation increment = 0.83; 95%CI = 0.69-1.00). In contrast, we did not observe significant associations between pre-diagnosis intake of total fruits, orange/yellow, white, and uncategorized groups and OC survival. Conclusion: Pre-diagnosis FV intake from various color groups, especially the green and red/purple ones, may improve OC survival. Further studies are needed to validate our findings.