Modelling the Impact of Reducing Ultra-Processed Foods Based on the NOVA Classification in Australian Women of Reproductive Age

Dietary Strategies to Reduce Triglycerides in Women of Reproductive Age: A Simulation Modelling Study

Many women of reproductive age have poor diet quality and are at higher risk of chronic diseases such as diabetes. Triglycerides are a critical risk factor for chronic diseases, and although they can be influenced by diet, there are minimal dietary intervention studies identifying key foods/food groups that reduce triglycerides. We performed data simulation modelling to estimate the potential reductions in fasting triglycerides that could be achieved by different dietary strategies in reproductive age women. The model was created using data from the 2011-2013 Australian Health Survey and incorporated various factors such as demographics, nutrient intake, and plasma biomarkers. Multiple linear regression analysis was conducted to estimate triglyceride levels, considering nutrient intake and pre-determined covariates. Dietary scenarios were developed, reducing the consumption of processed/ultra-processed foods, while increasing the intake of minimally processed foods like fruits, vegetables, fish, and nuts. A total of 606 women were included. Reducing processed foods by 50% plus increasing intakes of fruits (75-225 g/day), vegetables (75-225 g/day), or nuts (10-40 g/day) decreased triglycerides by up to 4.3%. Additionally, incorporating 80 g/day of omega 3 fish (>800 mg long-chain omega 3/100 g) decreased triglycerides by 8.2%. The clinical relevance of lowering triglycerides for cardiometabolic disease management should be tested in dietary intervention studies in women.

The mediatory role of inflammatory markers on the relationship between the NOVA classification system and obesity phenotypes among obese and overweight adult women: a cross-sectional study

Background

Diet and inflammation both play important roles in the occurrence of obesity. We aimed to investigate the role of inflammation in the development of both metabolically healthy obese (MHO) and metabolically unhealthy obese (MUHO) individuals.

Methods

This cross-sectional study included 221 overweight and obese women aged 18-56 years. The study assessed the metabolic health phenotypes of the participants using the Karelis criterion score. Additionally, dietary intakes were evaluated using a 147-item semi-quantitative questionnaire and the NOVA classification system (comprising 37 food groups and beverages). The study also collected and analyzed the blood parameters, as well as biochemical and anthropometric indices, for all participants.

Results

Among the women included in the study, 22.9% had MHO phenotypes but 77.1% had MUHO phenotypes. A significant association between the third quartile of the NOVA classification system and the increased likelihood of having the MUHO phenotype was observed (OR = 1.40, 95% CI = 1.09-4.92, p = 0.04). Regarding the potential role of inflammatory markers, high-sensitivity C-reactive protein (hs-CRP) (p = 0.84), transforming growth factor-β (TGF-β) (p = 0.50), monocyte chemoattractant protein-1 (MCP-1) (p = 0.49), plasminogen activator inhibitor-1 (PAI-1) (p = 0.97), and homeostatic model assessment for insulin resistance (HOMA-IR) (p = 0.92) were found to be mediators.

Conclusion

We observed a significant positive association between ultra-processed food (UPF) consumption and the MUHO phenotype in overweight and obese women. This association appeared to be mediated by some inflammatory markers, such as hs-CRP, TGF-β, MCP-1, PAI-1, and HOMA-IR. Additional studies are needed to validate these findings.