Dietary patterns and their association with the components of metabolic syndrome: A cross-sectional study of adults from northeast Thailand

Saturated fats network identified using Gaussian graphical models is associated with metabolic syndrome in a sample of Iranian adults

BACKGROUND

Gaussian graphical models (GGM) are an innovative method for deriving dietary networks which reflect dietary intake patterns and demonstrate how food groups are consuming in relation to each other, independently. The aim of this study was to derive dietary networks and assess their association with metabolic syndrome in a sample of the Iranian population.

METHODS

In this cross-sectional study, 850 apparently healthy adults were selected from referral health care centers. 168 food items food frequency questionnaire was used to assess dietary intakes. Food networks were driven by applying GGM to 40 food groups. Metabolic syndrome was defined based on the guidelines of the National Cholesterol Education Program Adult Treatment Panel III (ATP III).

RESULTS

Three GGM networks were identified: healthy, unhealthy and saturated fats. Results showed that adherence to saturated fats networks with the centrality of butter, was associated with higher odds of having metabolic syndrome after adjusting for potential confounders (OR = 1.81, 95% CI 1.61-2.82; P trend = 0.009) and higher odds of having hyperglycemia (P trend = 0.04). No significant association was observed between healthy and unhealthy dietary networks with metabolic syndrome, hypertension, hypertriglyceridemia and central obesity. Furthermore, metabolic syndrome components were not related to the identified networks.

CONCLUSION

Our findings suggested that greater adherence to the saturated fats network is associated with higher odds of having metabolic syndrome in Iranians. These findings highlight the effect of dietary intake patterns with metabolic syndrome.

Public health research needs for molecular epidemiology and to emphasize homeostasis - could the omnipotent endopeptidase inhibitor α-2-macroglobulin be a meaningful biomarker?

Public health authorities in low- and middle-income countries face dramatic challenges in handling rapidly increasing non-communicable diseases (NCDs), due to the epidemiological- and particularly nutritional transition. Among major reasons for the development of NCDs are smoking and alcohol, but overnutrition and obesity are also major threats to population health. Obesity is related to diabetes and cancer, but also has a genetic background. It is difficult to recommend a healthy nutrition. This is because of conflicting nutritional conceptions, and given the complexity of human metabolism understanding this topic can be difficult for the laymen.  Public health measures advocating physical activity and refraining from high intake of energy, sugar and soft drinks need to be enhanced by supporting the ‘intrinsic motivation’ to preserve a good health. The mission of public health should be to increase awareness about the complexity of human metabolism, and the involvement of genetic and epigenetics in health and diseases. To maintain homeostasis, means to keep an optimal relationship between catabolism and synthesis, seems to be of particular interest. Preconditions for this is, that public health institutions within the administration- and academic sector follow up developments in life science and molecular biology and conduct population-based research making use of molecular epidemiology, especially those related to key metabolic steps and maintenance of ‘homeostasis’, in balancing catabolism and anabolism. A prospective biomarker for this situation might be α-2-macroglobulin.