Triple whammy: Poor diets increase the risk of CVD by influencing obesity and depressive symptoms – China study
To investigate whether obesity, depressive symptoms, or a combination of the two, mediate the relationship between diet quality and CVD, a cross-sectional study was conducted by Qingdao University’s Department of Epidemiology and Health Statistics, School of Public Health.
The study analysed data from four cycles of the National Health and Nutrition Examination Survey (NHANES) performed between 2011 and 2018, and the United States Department of Agriculture’s (USDA) Food Patterns Equivalents Database (FPED).
A total of 12,644 participants were included in the study.
The Healthy Eating Index (HEI)-2015, which has a maximum score of 100, was used to assess dietary quality. The higher the score, the better the diet quality of participants.
Among 13 components of the HEI-2015, nine include whole fruits and grains, dairy, seafood and plant proteins, and fatty acids. A higher intake gives a higher score.
The other four moderation components are refined grains, sodium, added sugars, and saturated fats. A lower intake means a higher score.
Obesity was defined as a BMI of more than 30, in accordance with World Health Organization’s standards.
By predicting a 10-year CVD risk score using the Framingham Heart Study’s multifactorial calculation tool, the risk of heart disease in participants was divided into two categories — low (20% or lower) and high (20% or higher).
Depressive symptoms were recorded using a nine-item questionnaire. Participants were asked to choose one out of four answers for each question. Each answer had a score range of 0 to 3 points. The participants were then segregated into two groups (those with or without depressive symptoms) based on a cut-off of 10 points.
Findings from the analysis showed that higher HEI-2015 scores were associated with a lower risk of CVD.
The association was also found to be mediated by obesity, depressive symptoms, and their combined effects, with proportional mediations of 9.03%, 2.23% and 0.25% respectively.
“After controlling for confounding factors, we discovered that the mediating effect of obesity and depressive symptoms on the relationship between the HEI-2015 and CVD was statistically significant (p < 0.05), both separately and jointly,” said the authors.
Dietary interventions
Existing evidence suggests that a complex set of several nutrients may interact with genetic factors to influence CVD risk, which underscores the importance of dietary patterns.
In addition, previous studies have highlighted that higher dietary sodium intake elevates the risk of depression risk factors, such as high blood pressure, which may consequently affect neurological function.
“Our analysis of the correlation between the 13 components of the HEI-2015 and CVD indicated that increased intake of greens and beans, fatty acids, and seafood and plant proteins, as well as decreased consumption of sodium, refined grains and saturated fats are associated with low CVD risk,” the authors explained.
It was also found that people who are obese are at greater risk of developing depressive symptoms.
At the same time, studies have noted that depressive symptoms interact with CVD risk factors, such as smoking and hypertension, in a statistically significant way.
“Depressive symptoms are risk factors for CVD, and comorbidities between depression and CVD worsen the prognosis of patients. Therefore, active dietary interventions to reduce the occurrence of obesity and depressive symptoms should form a crucial part of CVD management strategies,” the authors added.
The strengths of this study are the large number of participants involved and the stratified sampling of the NHANES.
However, it was limited by the lack of conclusions on cause and effect, and control over certain covariates due to unknown or difficult-to-measure data.
Source: Nutrients
https://doi.org/10.3390/nu15030629
“The Chain-Mediating Effect of Obesity, Depressive Symptoms on the Association between Dietary Quality and Cardiovascular Disease Risk”
Authors: Shuai Zhang, et al