Consumption of unprocessed or minimally processed foods and their association with cardiovascular events and cardiometabolic risk factors in Brazilians with established cardiovascular events.
Aline Rosignoli da ConceiçãoAlessandra da SilvaAline MarcadentiÂngela Cristine Bersch-FerreiraBernardete WeberJosefina BressanPublished in: International journal of food sciences and nutrition (2023)
Consumption of food in its natural form has an inverse relationship with cardiometabolic risk factors; however, the relationship between consumption of unprocessed or minimally processed foods and the presence of cardiovascular diseases (CVD) remains unclear in individuals receiving secondary care for CVD. Thus, we aimed to evaluate the association between the consumption of unprocessed or minimally processed foods and the presence of CVD and cardiometabolic risk factors in individuals with established CVD. Baseline data from 2357 participants in a Brazilian multicentre study showed that the consumption of unprocessed or minimally processed foods corresponded to most of the daily caloric intake (69.3%). Furthermore, regression analyses showed that higher consumption of unprocessed or minimally processed foods (>78.0% of caloric intake) was associated with a lower prevalence of elevated waist circumference (WC1; PR: 0.889; CI: 0.822-0.961; WC2; PR: 0.914; CI: 0.873-0.957) and overweight (PR: 0.930; CI: 0.870-0.994), but also was associated with simultaneous occurrence of coronary and peripheral artery disease and stroke (OR: 2.802; CI: 1.241-6.325) when compared with a lower intake (<62.8% of caloric intake). These findings reinforce the importance of nutritional guidance that considers the profile of the target population and the composition and quality of the meals consumed.
Keyphrases
- cardiovascular events
- risk factors
- coronary artery disease
- cardiovascular disease
- weight gain
- body mass index
- healthcare
- peripheral artery disease
- physical activity
- coronary artery
- palliative care
- risk assessment
- type diabetes
- heart failure
- quality improvement
- metabolic syndrome
- machine learning
- left ventricular
- artificial intelligence
- subarachnoid hemorrhage
- electronic health record
- chronic pain