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Dietary Patterns (Poster Session)

(P22-021-24) Joint Associations of Quantity and Metabolic Quality of Fruits and Vegetables With Circulating Biomarkers of Inflammation, Adipokines, Insulin Response and Lipids

Monday, July 1, 2024
11:45 AM – 12:45 PM CT
Location: Poster Board 297
Disclosure(s):
Zahra Aslani, Master: No relevant financial relationship(s) with ineligible companies to disclose.


Objectives: Guidelines to increase fruit and vegetable (FV) consumption are based mainly on intake quantity, while quality is less often considered. We defined the dietary quality of 36 FV items based on their associations with 14 circulating metabolic biomarkers, then examined the role of overall quantity and metabolic quality on these markers.

Methods: Among 36,643 postmenopausal women in the Women’s Health Initiative with biomarker data, FV intake was assessed at baseline via food frequency questionnaire. The 14 biomarkers were grouped as: inflammation, adipokines, insulin response, lipids. An FV score ≥2 (range: -4 to +4), reflecting ≥1 favorable association in any two biomarker groups, qualified as high-metabolic quality. Multivariable-adjusted linear regression determined the individual and joint associations of quantity and quality with individual biomarkers and four z-scores.

Results: Among 36 FVs, 22 were identified as high-metabolic quality (highest quality: broccoli, salad, dried fruit; lowest quality: french fries, watermelon/red melon, fruit juices). Higher intake of high-metabolic quality FVs was associated with lower insulin hypersecretion, lower inflammation, and lower hyperlipidemia across levels of FV quantity. Comparing highest vs lowest metabolic quality tertiles, the βs (%) (95%CI) for inflammatory z-score were -5.43 (-11.7, 0.88), -14.3 (-20.9, -7.68) and -18.7 (-25.7, -11.6) in quantity tertiles 1-3. Similar findings were observed in joint analysis, e.g., for insulin response z-score, compared to participants with both lowest FV quantity/quality, the βs for those with higher total quantity comprised of high-metabolic quality items were: -17.6 (-24.5, -10.6), -25.9 (-32.6, -19.2), and -28.7 (-35.1, -22.2) in quantity tertiles 1-3, respectively.

Conclusions: Using metabolic quality of FVs to prioritize the increased uptake of certain FVs (in proportion to all FVs) may aid in achieving a favorable profile of biomarkers indicative of metabolic health.

Funding Sources: The WHI is funded by NIH-NHLBI.