3.2. Dietary Pattern/Principal Component Analysis
To identify the main dietary patterns present in our population, we performed PCA on reported macro and micronutrient intakes collectively (
Table S1). Three dietary patterns (PCs) each independently explained greater than 5% of the nutritional variance and were used for further analyses. PCs 1–3 explained 10.5%, 9.3%, and 6.5% of the nutritional variation, respectively. Collectively these PCs explained 26.3% of the total variance (
Table S1). Because gender may alter the dietary patterns produced in our analyses, we also performed PCA separately in each gender. Comparison of the PC loadings from the combined analysis and gender subset analyses were highly correlated (
p < 2.2 × 10
−16 for all PCs; data not shown), thus PCs generated from the combined analysis were used for further studies. Nutrients with an absolute loading value greater than 0.15 were considered to contribute significantly to the dietary pattern. PC1 was negatively correlated with vitamin, mineral, fiber and protein consumption, termed vitamin and mineral intake. PC2 was negatively correlated with folate, carbohydrate, and fiber intake while positively correlated with monounsaturated fatty acid (MUFA) and saturated fatty acid (SFA) intake, termed SFA:carbohydrate. This PC was associated with high saturated and monounsaturated fat and low carbohydrate/fiber intake. PC3 was negatively correlated with SFA, carbohydrate, sugar and calcium consumption while positively correlated with MUFA/polyunsaturated fatty acid (PUFA) consumption, i.e., low carbohydrate and SFA high MUFA/PUFA intake, termed SFA:PUFA. To increase interpretability of dietary pattern analyses we grouped the PCs into quartiles. The mean nutrient intake for each PC quartile stratified by gender is shown in
Table S2. The proportion of change was similar between genders for significantly associated nutrients. The average reduction in vitamin, mineral, fiber, and protein (PC1) intake was 50 (males) and 48% (females) between the highest quartile (Q1) and the lowest quartile (Q4). For PC2, the average reduction in folate, fiber and carbohydrates was 41% for males and females, respectively, while the average increase in SFA and MUFA was 1.58 and 1.66 fold for males and females respectively. For PC3, the average reduction in SFAs and sugars was 53 (males) and 50% (females) from the highest quartile (Q1) to the lowest (Q4). The average increase in PUFA and MUFA was 1.77 and 2.25 fold. A large proportion of this increase was attributable to PUFA22:5, docosapentaenoic acid which increased 7.5 and 13 fold in both males and females respectively.
3.3. Dietary Pattern Associations with Lipid Levels
We characterized the association of dietary patterns (PC1-3) with lipid levels separately in males and females to better understand the influence of gender. Results were considered significant if they met multiple testing correction of 0.00238 when testing separately in each gender and 0.00714 when testing for an interaction both assuming an additive model (
Table S3). Vitamin and mineral intake (PC1) was significantly correlated with three of the four lipids tested (
Figure 1A). HDL cholesterol was negatively correlated with PC1 in females (
padd = 4.30 × 10
−4) but not males (
padd = 0.986). This effect was significant for an interaction with gender (
pint = 1.42 × 10
−6), and suggests that increasing dietary intake of vitamin and minerals is correlated with reduced risk of low HDL cholesterol levels in females only. TG levels were positively correlated with PC1 in females (
p = 1.2 × 10
−4) indicating low vitamin and mineral intake was associated with elevated blood TG. Among males, TG levels were trending toward an association (
p = 0.00440). No interaction was observed between genders (
pint = 0.942), suggesting that reduced vitamin and mineral consumption sequentially increased TG levels in both genders albeit to a lesser degree in males. Finally the TC:HDL cholesterol ratio is significantly correlated with vitamin and mineral levels in females (
p = 1.3 × 10
−4), and trending in males (
p = 0.0267). The results in both genders were consistent with reduced vitamin and mineral consumption correlated with risk of elevated TC:HDL cholesterol ratio. We note that although fiber is well known to influence lipid levels [
28], removing the effects of fiber via inclusion in our regression model dampens but does not abrogate the association between PC1 and HDL cholesterol (
padditive = 0.99 (males), 4.3 × 10
−4 (females)), TG (
padditive = 0.049 (males), 0.0018 (females)) or TC:HDL cholesterol ratio (
padditive = 0.23 (males),0.008 (females)), suggesting that fiber does not contribute to the entirety of the observed association.
PC2 (increased SFA: reduced carbohydrate intake) was not significantly associated with lipid levels, however there were many nominal associations (
Figure 1B). Increasing female TG levels were modestly correlated with decreasing SFA/MUFA and elevated carbohydrate and fiber consumption (
padd = 0.029). While this may seem counterintuitive, increasing carbohydrate levels in the presence of reduced SFA are known to increase TG levels [
29,
30]. Males appear unchanged (
padd = 0.627). Additionally both male and female LDL cholesterol level increases were nominally associated with low SFA and MUFA and high fiber/folate intake (
padd = 0.0368 and 0.0396 for males and females respectively), corresponding with the literature demonstrating that increasing carbohydrates while reducing SFA intake is known to increase LDL cholesterol levels [
31]. Finally, the TC:HDL cholesterol ratio was positively correlated with PC2 at a nominal
p-value of 0.0382 in males, while females showed no evidence of an association (
p = 0.289). The substitution of fatty acids for carbohydrates was beneficially associated with HDL cholesterol metabolism [
32], consistent with male results. Although not significant the observed correlative trends were also present in the literature and demonstrate possible interactions with gender for TG and TC:HDL cholesterol ratio that should be further explored.
PC3, high intake of SFA, carbohydrates, sugar and calcium and low intake of MUFA/PUFA were negatively associated with TG levels in males and females, i.e., increased MUFA/PUFA consumption at the expense of SFA intake was associated with reduced TG levels in both genders (
padd = 1.50 × 10
−4 and 2.10 × 10
−4 for males and females respectively). Conversely, HDL cholesterol was positively correlated with PC3 in males (
padd = 2.5 × 10
−4) and trends were observed in females (
padd = 0.0403), suggesting that increased SFA and reduced MUFA/PUFA correlated with reduced risk for low HDL cholesterol in both males and females. An interaction with gender was not detected for either lipid (
pint = 0.616 and 0.409). TC:HDL cholesterol ratio was trending toward an association with PC3 in females (
p = 0.0205) and males (
p = 0.064). The majority of the observed associations with PC3 were observed in both genders suggesting these effects may not vary by gender and demonstrate well documented associations of reduced SFA and increased PUFA intake on lipid profiles [
5,
7].
We re-analyzed the dataset using a Caucasian only subset and individuals not on lipid modifying drugs only, to assess the influence of ethnicity and lipid modifying medication usage on our results. The same trends were observed in both the full and subset analyses (
Table S4). Collectively dietary pattern analyses support the literature demonstrating the association of common dietary patterns with lipid fluctuation while identifying previously unknown gender interactions that may explain variability in reported associations as well as help to increase our understanding of nutritional association with lipid variation in the U.S. population.
3.4. Age, Gender and Dietary Pattern Associations with Lipid Levels
Age is known to alter the absorption or subsequent processing of nutritional components, therefore to investigate the effect of age on significant gender-associations we repeated our previous linear regression analysis under an additive model (
Table 2). As TG levels are strongly associated with both genders in PCs 1 and 3 these analyses were combined. The association of HDL cholesterol with vitamin and mineral intake (PC1) in females was significant in the young (
p = 1.94 × 10
−4;
β = −1.93 mmol/L) to middle (
p = 0.027;
β = −0.95 mmol/L) age demographic with no association in older individuals (>65;
p = 0.817;
β = −0.16 mmol/L). Indicating that physiological differences between men and women of child bearing age may interact with vitamin and mineral consumption to modulate the risk of low HDL cholesterol in women. Improvement of TG level correlation with increased vitamin and mineral consumption was observed in all age groups (
p < 0.05). Although a similar trend was observed in males and females for TC:HDL cholesterol ratio, i.e., improvement was associated with increased vitamin and mineral consumption, the age association results are different. Males show a modest association overall, however associations appear strongest in young and older individuals. The association in females was much stronger in younger individuals and tapers off with increasing age (
p = 3.26 × 10
−4 vs.
p = 0.42;
Table 2).
The modest improvement (reduction) in HDL cholesterol levels with increasing MUFA/PUFA and decreased SFA intake (PC3) in males was significant or trending in all age groups. TG trends with PC3 were also detected in all age groups (
p < 0.1;
Table 2). These analyses suggest that in addition to minimal gender alterations, PC3 associations may not be affected by age. Collectively, these age analyses build on the gender effects observed previously, and add information on age associations that are necessary for study interpretation.
3.5. Individual Nutrient Consumption Associations with Lipid Levels
In an effort to expand on dietary pattern analyses and identify individual nutrients that may influence lipid levels (
p < 0.000833;
Figure 2;
Table S5) we analyzed the dietary intake data on a nutrient by nutrient basis. Carbohydrate and sugar intake were negatively correlated while alcohol intake was positively correlated with HDL cholesterol levels in both genders (
Figure 2A;
Table S5), consistent with the literature [
33,
34]. Magnesium intake was positively associated with HDL cholesterol levels in females only. We did not observe an association with age (
Table S6), suggesting this association may be independent from the dietary pattern analysis. Additional female-specific associations (Vitamin E and Copper) were also observed. Copper was previously shown to be negatively associated with HDL cholesterol levels in children [
35] and among a predominantly female population of adults [
36]. Vitamin E was associated with reduced HDL cholesterol levels in animal [
21,
37] and adult human [
38] studies. Finally, we also report a male-specific effect of retinol intake, such that reduced intake of retinol was associated with increased HDL cholesterol. Note that while these associations were statistically significant and novel the effect was modest making detection in gender-corrected studies less likely.
TG levels were negatively correlated with vitamin E and magnesium intake in both genders, consistent with the literature [
39,
40] (reviewed in [
41]). Among males, lutein and PUFA intake were negatively correlated with TG (
Figure 2B;
Table S5). The intake of good fats (PUFAs) are known to reduce TG levels [
7,
8], consistent with this observation in males. However, PUFA intake was not correlated with TG levels in females. Additionally, carbohydrate and sugar intake were positively correlated with TG levels in females only. This female-specific correlation of increased carbohydrate/sugar intake with TG levels was consistent with dietary pattern analysis in which PC2 SFA vs. carbohydrate intake was nominally associated with TG levels in females but not males in the same manner (
Figure 1B). Moreover, females have a much lower intake of SFA than males (
p < 2.2 × 10
−16,
β = −7.3). High carbohydrate:SFA ratio was associated with increased TG levels [
5]. To this end we tested the association of TG with carbohydrate intake by quartiles of carbohydrate:SFA ratio, to test if the correlation of carbohydrates with TG increases with increasing SFA:carbohydrate ratio. As expected, among females but not males, we observed that the correlation between TG and carbohydrate increased as the ratio of carbohydrates to SFA increased (
Table S7), highlighting nutritional/behavioral differences between genders that result in different nutrient phenotype correlations.
There were few individual nutrient interactions with LDL cholesterol. Caffeine and MUFA16:1 were positively associated with LDL cholesterol levels (
p = 5.02 × 10
−5) (
Figure 2C;
Table S5). The ratio of total cholesterol to HDL cholesterol was positively correlated with sugar and negatively correlated with alcohol, fiber, and vitamin E in both genders (
Table S5). Magnesium was negatively while copper was positively correlated with TC:HDL cholesterol in females only. Among males PUFAs (Total PUFA, PUFA 18:2, and PUFA 18:3) were negatively correlated while MUFA 16:1 was positively correlated with TC:HDL cholesterol ratio, consistent with the literature where increased PUFA intake reduces TC levels and raised HDL cholesterol levels [
32]. The gender associations in the ratio likely reflect the gender associations observed in HDL cholesterol and TG. As TC to HDL cholesterol ratio is considered to be a very good predictor of specific types of cardiovascular disease risk [
5] further understanding of nutritional and gender interactions is warranted. Furthermore, an understanding of how the different components that make up the phenotypes (i.e., TC:HDL cholesterol ratio involves LDL cholesterol, TG, and HDL cholesterol) are involved with the outcome of interest can increase interpretation of relevant phenotypes and further promote understanding of potential nutritional intervention and treatment.
3.6. Age, Gender and Individual Nutrient Associations with Lipid Levels
To test if significant nutrient level correlations with lipid levels varied by age, we subset the individual nutrient data by gender and age groups (18–35, 36–64, ≥65) and repeated the linear regression analyses (
Table S6). Among males, HDL cholesterol levels were correlated with carbohydrates, sugar, and alcohol consumption in all age groups, however alcohol consumption showed an interaction with age such that increased alcohol intake was associated with a larger improvement in HDL cholesterol levels as males aged (
pint = 0.00136). The entirety of the male-specific retinol association with HDL cholesterol levels was observed in the 36–64 year age group (
p = 2.87 × 10
−8;
p = 0.82 and 0.35 for ≤35 and ≥65 age groups respectively). Among females HDL cholesterol levels were associated with folate and alcohol in an age specific manner. Associations with HDL cholesterol levels and alcohol consumption increased with age while the correlation with folate intake and HDL cholesterol levels decreased with age.
Among males, TG levels were correlated with significant individual nutrient intake in all age groups. Vitamin E levels trended toward an interaction (
p < 0.05) with age such that increasing age displayed a more prominent improvement in TG levels. This effect was not observed to the same degree in females (
pint = 0.72). Female-specific carbohydrate and sugar associations were correlated with age such that older females demonstrated a larger inverse association with TG levels (
pint = 0.0084 and 0.03, respectively). TC:HDL cholesterol ratio showed many age associations. Sugar demonstrated a positive association with TC:HDL cholesterol levels and this association strengthened with age in males (
pint = 6.68 × 10
−3). The negative correlation of PUFA intake with TC:HDL cholesterol ratio also showed evidence of age associations in males (
pint = 0.032). Magnesium, copper, and fiber intake were negatively correlated with TC:HDL cholesterol ratio in females. This association also decreased with age (
Table S6).