Objective:The objective of this study was to review the most commonly used edible oils and fats in India, determine their effect on lipid profile and anthropometric parameters and study their association with the development of NCDs such as cardiovascular diseases and diabetes.

Methods:A comprehensive literature search was conducted using a combination of search terms by two independent researchers using PubMed from 2010 to January 2019. Studies including adult population evaluating the effect of different vegetable oils and fats via both observational and experimental designs were included. Reviews of studies in similar area were also included. The searches were managed in Mendeley, and duplicate entries were removed. Titles and abstracts of retrieved articles were screened by two reviewers. A tailored data abstraction tool was used to record characteristics of included studies, such as location, outcomes assessed, findings and demographics, by the study authors. Furthermore, data on the parameters compared and outcomes measured were recorded for quantitative studies.

Results:In total, 34 articles were reviewed. Vanaspati and ghee were the most commonly used oils and fats in the Northern states of India, whereas groundnut oil was preferred in the Southern and Western states. All forms of coconut oil, including virgin- and extra-virgin forms, showed an overall beneficial effect on anthropometric parameters, with decreases in BMI, waist circumference and neck circumference and an increase in lean muscle mass. Coconut oil has been linked to improved lipid profile, and sunflower oil and ghee also showed similar effects. Intake of >1.25 kg/month of ghee along with <0.5 L/month of mustard oil have been reported to cause a decrease in total cholesterol levels. Overall, 15 studies reported that coconut oil has a protective effect on cardiovascular health. Owing to its anti-inflammatory effects, olive oil has been associated with a decreased risk for diabetes.

Results : The validation statistics indicated the accuracy of WHO/ISH risk prediction chart in identifying cases with CHD with 60.0% sensitivity and 93.2% specificity. A minimum of 9 risk factors for developing CHD were detected among each patient in the study cohort (p<0.0001). Hypertension was the strongest predictor of CHD [OR, (95% CI): 20.8 (5.6-76.9)]. Silent CV risk factors were found in about 30% of the studied population. The latter did not differ significantly by gender. We propose a different risk assessment model for general practice that incorporates standard CV risk factors with or without laboratory tests.