Adult Gender and Age Healthy Eating Index Models Predict Cardiometabolic Risk Factors in Cross-Sectional Study | BMC Nutrition
Relationship between the components of the SEA
The correlations between the HEI component and the total scores were assessed to determine the amount of unique information contained in each HEI component. The total HEI score had moderate to weak correlations with the individual scores of the HEI components, but the HEI components showed many significant correlations (P r> 0.1; m = 378; Supplementary table 3). Among these, strong correlations were observed between âtotal fruitsâ and âwhole fruitsâ (r = 0.87) and âfatty acidsâ and âsaturated fatsâ (r = 0.73). Moderate correlations were observed between ‘green vegetables and beans’ and ‘total vegetables’ (r = 0.63) and âseafood and vegetable proteinsâ (r = 0.45), âtotal vegetablesâ and âadded sugarsâ (r = 0.43), and between âdairy productsâ and âfatty acidsâ (r = – 0.42), and between âtotal proteinsâ and âseafood and plant proteinsâ (r = 0.40). All other observed correlations were weak (r 0.4).
Dietary differences with age, gender, and cardiometabolic risk factors
Overall, total IES scores were similar between genders and were higher (P
Numerous gender-dependent differences in the HEI components have been detected. Women scored higher for ‘total vegetables’ and ‘whole fruits’ (PP= 0.03) than men (Supplementary Table 2). Among females, the highest scores also approached significance for ‘total fruit’ (P= 0.07), ‘milkman’ (P= 0.09), and “refined grain” (P= 0.1), as did the lower scores for ‘total protein’ (P= 0.06) and âadded sugarsâ (P= 0.06). Men aged 18 to 33 had lower ‘total fruit’ and ‘whole fruit’ scores than other age categories (PPP
CMdrf group ranking
Of the 393 participants, 286 were stratified into the high CMDrf group with either 1 (m= 71; m= 62), 2 (m= 39; m= 31), or 3+ (m= 47; m= 36) risk factors for women and men, respectively. Notably, participant selection was stratified to provide balanced coverage based on gender and age of normal, overweight, and obese participants, which may oversample the high CMDrf group in the geographic area. Anyway, only 25% (m= 99) of participants had a BMI> 25 kg / m2 as the sole risk factor. Of the 31 participants without clinical blood measurements, 25 were classified in the high CMDrf group by BMI. Among participants with a BMI and clinical blood measurements, only 5% were classified as high risk with a BMI 2. Therefore, of the 6 participants classified in the low CMDrf group on the basis of BMI without supporting clinical measures, it is estimated that 2 could be misclassified. This would represent a misclassification rate of 0.5% and was found to be acceptable. With these caveats, the phenotyping cohort was stratified into low (m= 107; ~ 27%) and high (m= 286; ~ 73%) CMDrf groups that differed (PPP= 0.10) in the high CMDrf group in participants aged 34-65 vs. 18-33 (115 vs. 90 mg / dL). Only 15 participants were smokers and were not associated with specific CMDrf groups.
Food score differences between CMDrf groups
Of the 393 participants, HEI scores were calculated for 378 who performed two or three 24-hour recalls. The high CMDrf group had a lower total HEI score than the low CMDrf group (total HEI score 60 vs. 66, respectively; P
Gender-specific differences between the high and low CMDrf groups in the HEI components of “total fruit”, “whole fruit”, “total vegetables”, “green vegetables and beans”, “dairy”, “seafood protein” and of plants â,â sodium â, the scoresâ fatty acids âandâ saturated fats âwere observed (P
HEI component-based prediction of the presence of CMD risk factors
As several gender and age differences in the scores of the components of the IES were identified (Supplementary Table 2), models were constructed to assess the age x sex categories (Supplementary Tables 5, 6 and 7). The prediction of the CMDrf group based on the HEI components was excellent for females and good for males in all age groups. (Table 2, additional Fig. 2). The frequency of inclusion of HEI components by stepwise discriminant analysis in the six age x sex models was “dairy” = “total vegetables” = “saturated fat” (m= 6; 100%)> “green vegetables and beans” = “total protein” = “refined grains =” ââfatty acids “(n =5; 83%)> ‘whole grains’ = ‘total fruits’ = ‘seafood and vegetable proteins’ (m= 4; 66%)> ‘whole fruit’ = ‘added sugars’ = ‘sodium’ (m= 3; 50%) (Supplementary Table 8).
The accuracy of the classification of the CMDrf group of food components showed high sensitivity (91% accuracy) depending on gender and age (Table 3). However, the specificity of the model depended on age, increasing with age: young (78%)
‘Dairy’, ‘total vegetables’ and ‘saturated fat’ were the HEI components common to all CMDrf diet-based prediction models for all genders and ages. The mean profiles of the HEI components of the predicted CMD risk groups are shown in Supplementary Table 11 and parallel the results reported in Figure 2.
Models of risk factors in high or low CMDrf groups predicted by diet
Finally, we evaluated how the prediction of the CMDrf group based on the HEI components separated the CMD risk factors used for stratification and other clinical parameters associated with cardiometabolic health. As expected, BMI, fasting insulin, and HOMA were higher in both sexes across all age categories in the high CMDrf group (PPPPP= 0.01; Table 4). For participants over 30, the mean risk of Framingham (%) was also higher (P= 0.03) in 5.5% in the high groups versus 4% in the low CMDrf groups, but the interactions between sex and risk were not significant (P= 0.07).