Clinical Research Directory

Workplace Intervention Including Exercise and Nutrition in Obese Office Workers

The main objective of this study is to investigate the efficacy of a 6-month workplace combined (exercise and nutrition) intervention in obese office workers, using a randomized controlled study. An additional objective of this study is to evaluate the individual responses per participant following the program.

Assess the Effects of Replacing Foods High in Refined Carbohydrates With Avocado on Biomarkers of Inflammation.

The objective of this trial is to assess the effects of replacing foods high in refined carbohydrates, particularly added sugars, with avocado (isocaloric substitution) on biomarkers of inflammation and insulin sensitivity in adults with elevated hs-CRP and central adiposity. Eligible participants will complete two 4-week interventions (1 avocado/d and control) separated by a 2-week washout phase. Participants will complete a total of 7 clinic visits including one screening visit (visit 1, -7 days), one baseline visit (visit 2, day 0), two visits during each 4-week diet condition (visit 3 \& 6 on day 21 and visits 4 \& 7 on day 28), and one visit at the conclusion of the washout phase/start of the second condition (visit 5, day 0).

Comparison Between the Health Effects of an AI-driven Model With Those of Human Professional Guidelines for the Treatment of Obesity

Many non-communicable diseases are diet-related and have a significant impact on public health. It is stated that global dietary shifts are needed to change disease patterns, highlighting the importance of nutrition in addressing public health issues, such as obesity. The field of nutrition has been dependent on clinical and observational studies; however, the emergence of Artificial Intelligence (AI) is transforming these approaches. ChatGPT may be used to provide dietary recommendations due to its high speed, extensive access to a variety of meal data, and low complexity. However, initial evaluations have shown that ChatGPT may be inaccurate in terms of safety and reliability, and traditional nutrition approaches are highly reliant on experts' knowledge and the validity of nutritional guidelines. It has been suggested that AI in nutrition may be beneficial; however, further investigations are needed. Our proposal aims to fill the represented critical evidence gaps. The study aims to compare the health effects of an AI-driven model with those of human professional guidelines for the treatment of obesity. Furthermore, investigators seek better strategies to utilize AI, if appropriate, for weight loss and other health benefits.