Introduction

Technology helps to better understand nutrition and the microbiome, for the scientific community to  close the knowledge gap between bioinformatics and health informatics (1).

Microbiome is linked to various diseases(2). Through the metabolism and modification of different nutrients, the gut microbiota influences health outcomes by producing secondary metabolites that have varying retention durations, bioactivity levels, and impacts (3).

The amount of research and data available on this subject is anticipated to expand due to the declining prices of microbiome sequencing and the growing interest in the effects of the microbiome on health. The review’s literature focused on diet-related conditions that have significant effects on public health, such as obesity and overweight, type 2 diabetes, COVID-19, irritable bowel syndrome (IBS), irritable bowel disease (IBD), and food allergies/intolerances(1).

Diet and Gut Health’s Role in Disease

The diverse collection of bacteria called the gut microbiome that lives in our intestines is greatly influenced by our diet. Maintaining overall health, assisting with digestion, producing vitamins, and fending off infections all depend on a balanced gut microbiota. Poor eating practices such as eating processed foods and foods that have added sugars, saturated and trans fats, and are low in fiber, can upset this equilibrium and cause dysbiosis, which is connected to inflammation and a number of disorders that are diet-related (4).

Public Health Informatics

Informatics is the application of technology, information systems, and data to enhance health outcomes. Informatics makes it possible to gather, analyze, and understand enormous amounts of data about health in the field of public health. The detection of patterns, the forecasting of disease outbreaks, and the assessment of the efficacy of interventions are made easier by technologies like machine learning, big data analytics, and electronic health records (EHRs)(5).

Exploring Gut Health and Diet-Driven Diseases through Informatics

Several crucial tactics are involved in using informatics to investigate the relationship between diet-driven disorders and gut health:

  1. Data Collection and Analysis: Acquiring information on eating patterns, gut health indicators, and health outcomes through the use of EHRs and digital health records. Sophisticated analytical methods can be used to find connections and causes between gut health, illness, and nutrition.
  2. Microbiome Research: Use bioinformatics techniques to examine microbiome data and comprehend the intricate relationships that exist between gut microbes and their hosts. This study can pinpoint particular food ingredients that affect gut health and help avoid sickness.
  3. Predictive modeling: The process of estimating a person’s probability of contracting diet-related diseases by using machine learning algorithms to analyze their personal eating habits, gut health, and other risk variables. By using these models, high-risk populations can be identified and preventive interventions can be adjusted appropriately.
  4. Public Health Surveillance:  Involves putting in place real-time monitoring systems to keep an eye on illness incidence, dietary patterns, and indications of intestinal health. This strategy makes it possible to monitor the success of public health efforts and to take prompt action.
  5. Personalized Nutrition: Creating individualized nutrition programs based on food preferences, gut microbiota profiles, and personal health information is known as personalized nutrition. Customizing dietary recommendations to effectively prevent or manage diet-driven disorders can be made easier with the use of informatics(1,4).

Implications for Public Health

There are major public health implications to the use of informatics in the research of diet-related disorders and gut health. It permits a more accurate comprehension of the ways in which dietary habits and gut health affect general health and facilitates the creation of focused therapies. Data-driven insights can guide public health policy, resulting in more successful methods of illness prevention and health promotion(1,2,4).

Conclusion

There is a lot of potential to improve public health outcomes by using informatics to investigate diet-driven disorders and gut health. We can gain a deeper understanding of the intricate connections between gut health, disease, and food by utilizing cutting-edge analytical methods and data. This will help to reduce the burden of diet-related diseases on the public health system by paving the path for more successful interventions.

Reference

  1. Cooper, K., Clarke, M., & Clayton, J. B. (2023). Informatics for your Gut: at the Interface of Nutrition, the Microbiome, and Technology. Yearbook of medical informatics, 32(1), 89–98. https://doi.org/10.1055/s-0043-1768723
  2. Kwa, W. T., Sundarajoo, S., Toh, K. Y., & Lee, J. (2023). Application of emerging technologies for gut microbiome research. Singapore medical journal, 64(1), 45–52. https://doi.org/10.4103/singaporemedj.SMJ-2021-432
  3. Saxena, R., Sharma, V., Saxena, A. R., & Patel, A. (2024). Harnessing AI and Gut Microbiome Research for Precision Health. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 3(1), 74-88.
  4. Sekirov, I., Russell, S. L., Antunes, L. C. M., & Finlay, B. B. (2010). Gut microbiota in health and disease. Physiological Reviews, 90(3), 859–904. https://doi.org/10.1152/physrev.00045.2009
  5. Aziz, H. A. (2017). A review of the role of public health informatics in healthcare. Journal of Taibah University Medical Sciences, 12(1), 78–81. https://doi.org/10.1016/j.jtumed.2016.08.011