The association of obesity-related dietary patterns and main food groups derived by reduced-rank regression with cardiovascular diseases incidence and all-cause mortality: findings from 116,711 adults

Abstract

Purpose: Research about using reduced-rank regression (RRR) to simultaneously study the effects of both individual and combined consumption of foods on cardiovascular diseases (CVD) is scarce.

Methods: This study included 116,711 CVD-free participants (a median of 11.8 year follow-up) with 2 or more 24-h online dietary assessments. A total of 210 food items were classified into 45 food groups, and the mean amount of each food group was used in RRR to derive dietary patterns (DPs) explaining the maximum shared variation in obesity-related indicators. The associations of DPs and its main food groups (|factor loading| [Formula: see text] 0.2) with the incident CVD and all-cause mortality were examined by Cox model. In cross-sectional analyses, the associations of DP scores with cardiometabolic risk factors (biomarkers) were examined by linear regression.

Results: The derived DP was characterized by higher intakes of beer and cider, high-sugar beverages, processed meat, red meat, artificial sweetener, and crisps, chips and savory snacks, and lower intakes of olive oil, high fiber breakfast cereals, tea, and vegetable. Compared to the lowest dietary score quintile, those in the highest were associated with higher risks of total CVD (adjusted-HR: 1.45, 95% CI 1.33-1.57) and all-cause mortality (adjusted-HR 1.31, 95% CI 1.18-1.45). We observed consumption alone of these food groups had a consistent but limited health effect on total CVD and all-cause death incidence. These associations were modified by age and sex. Higher DP scores were related to adverse biomarkers profiles.

Conclusions: We developed obesity-related DPs prospectively associated with increased risks of CVD and all-cause mortality.

Keywords: Cardiovascular diseases; Dietary pattern; Obesity; Reduced rank regression.