Poster Presentation Nutrition Society of Australia 50th Annual Scientific Meeting 2026

Potential biological pathways linking MIND diet quality to cardiometabolic disorders: the role of metabolic, lipid and inflammatory biomarkers (144138)

Ayushi Goel 1 , Prachi Kulkarni 1 , Helen Macpherson 2 , Tanita Botha 3 , Sarah McNaughton 4 , Veer Gupta 1 , Catherine Milte 2
  1. Deakin Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Health, Deakin University, 75 Pigdons Rd, Waurn Ponds, Geelong, VIC 3216, Australia
  2. Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Burwood, Melbourne, VIC 3125, Australia
  3. Biostatistics Unit, Faculty of Health, Deakin University, 221 Burwood Highway, Burwood, Melbourne, VIC 3125, Australia
  4. School of Human Movement and Nutrition Science, University of Queensland, Brisbane, Queensland, Australia

Cardiometabolic disorders (CMDs) are increasing in middle-aged adults(1), yet the biological pathways linking the Mediterranean–DASH Intervention for Neurodegenerative Delay (MIND) diet, a dietary pattern developed for brain health, with circulatory biomarkers and subsequent cardiometabolic disease risk remain unclear(2). As a key modifiable risk factor, diet may influence cardiometabolic health through changes in metabolic, lipid, and inflammatory biomarkers(3). This study examined the associations between MIND diet quality, circulatory biomarkers, and incident CMDs in middle-aged Australian adults. A total of n = 709 adults aged 55-65 years from the Australian Wellbeing, Eating and Exercise for Long Life (WELL) prospective cohort completed postal surveys in 2010, 2012, and 2014, including a validated 111-item food frequency questionnaire. Diet quality was assessed using the MIND index. Circulatory biomarkers were evaluated from fasting blood samples collected in 2012. Multivariable linear regression examined associations between average MIND diet quality (2010–2012) and circulatory biomarker levels (2012). In secondary analyses, a subsample of n = 408 participants free of CMDs in 2012 was used to evaluate the associations between biomarkers (2012) and incident CMDs (2014), and between diet quality (2010–2012) and incident CMDs (2014), using covariate-adjusted logistic regression. Greater adherence to the MIND diet quality was associated with more favourable biomarker profiles after adjustments for covariates. Specifically, higher MIND diet quality was linked with lower serum insulin (β = −0.05, p = 0.01), HOMA-IR (β = −0.05, p = 0.02), and hs-CRP (β = −0.12, p = 0.003) in the overall population. Gender-specific differences were observed. In men, higher MIND diet quality was associated with lower serum insulin (β = −0.07, p = 0.028), HOMA-IR (β = −0.06, p = 0.04), and hs-CRP (β = −0.13, p = 0.02).  In contrast, among women, higher MIND diet quality was associated with lower triglyceride levels (β = −0.05, p = 0.006). In secondary analyses, higher levels of HbA1c (OR = 3.12, p = 0.012), plasma glucose (OR = 1.77, p = 0.009), triglycerides (OR = 1.91, p = 0.041), and hs-CRP (OR = 1.29, p = 0.01) were independently associated with increased odds of incident CMDs. However, after full adjustment, higher MIND diet quality was borderline associated with lower odds of incident CMDs in the total sample and men, but not in women. These findings suggest that greater adherence to the MIND diet was associated with more favourable circulatory biomarker profiles, including lower serum insulin, HOMA-IR, hs-CRP, and triglycerides, with notable gender-specific differences. Several biomarkers, including plasma glucose, HbA1c, triglycerides, and hs-CRP, independently predicted incident CMDs, suggesting that diet may influence cardiometabolic risk through biological intermediate pathways and highlighting diet quality as a modifiable target for CMD prevention in middle-aged adults. Future mediation analyses are warranted to confirm these mechanisms.

 

 

 

  1. Sarkar, S., Prasanna, V. S., Das, P., et al. (2024) Front Pharmacol, 15, 1447890
  2. Akbar, Z., Fituri, S., Ouagueni, A., et al. (2023) Diabetes Metab Syndr Obes, 16, 3353-3371
  3. Livingstone, K.M., Milte C.M., Torres S.J., et al. (2022) J Nutr, 152(3), 805-815