Findings from the cross-sectional analyses are consistent with results from several studies suggesting that higher total carbohydrate intake, percentage of calories from carbohydrate, GI and/or GL are related to lower HDL-C and higher serum triacylglycerols levels [12
]. An interesting finding from our study revealed that higher total carbohydrate intake, GL, or both are also related to lower total and LDL-C levels. To our knowledge, these associations have not been reported in previous studies [12
]. Although the inverse relationship between dietary carbohydrate and total cholesterol and LDL-C may appear to be beneficial, the overall impact on the lipid profile is still unfavorable because of a proportionally greater decrease in HDL-C, resulting in a relative increase in the TC:HDL-C ratio. On the other hand, this analysis confirmed a clearly unfavorable relationship between higher carbohydrate intake and elevated triacylglycerol levels [14
]. Both decreased HDL-C levels and increased triacylglycerol levels are related also to the development of metabolic syndrome and diabetes. Longitudinal analysis showed a significant increase in total cholesterol and LDL-C related to increasing GL, and a significant decrease in HDL-C and increase in total cholesterol/ HDL-C ratio related to percentage of calories from carbohydrates. Nonetheless, these observations also suggest that dietary CHOs have a complex relationship with serum lipids, which need to be further elucidated.
Increased carbohydrate consumption and intake of food with a high GI produces higher postprandial glucose and insulin concentrations [36
]. Ultimately, this may decrease insulin sensitivity [37
], raising fasting triacylglycerol concentrations and reducing HDL-C levels, a profile that increases the likelihood of CHD [38
]. Cross-sectional associations of carbohydrate factors with HDL-C and triacylglycerol concentrations are supported by findings reported in previous studies. Four of five epidemiological cross-sectional analyses published on the subject, including the Nurses' Health Study and examination of NHANES III data, demonstrated higher HDL-C levels and lower triacylglycerol levels among individuals in the lowest category of GI or GL as compared with those in the highest category, after adjustment for potentially confounding factors [11
]. Two of these studies compared GI and GL directly with respect to serum lipid concentrations. One found that GL had a greater effect [14
]; while in the other, both GI and GL had similar effects [12
]. The fifth observational study found no significant association between GI and metabolic risk factors for heart disease [25
]. Cochrane system review of 15 RCTs for low GI diet intervention also found little association between GI and serum lipids [40
In contrast to the cross-sectional analyses, there are many fewer associations observed in the longitudinal analyses: only a significant increase in total cholesterol and LDL-C related to increasing GL, and a significant decrease in HDL-C and increase in total and HDL-C ratio related to percentage of calories from carbohydrate. It is well known that even well-established predictors of serum lipids require relatively large changes in order to effect group-level change. This may also be true of carbohydrate factors, though this field is far from producing predictive equations of the type developed for dietary fat [41
Unlike intensive intervention trials, there were only small changes in either CHO intake or blood lipid levels over the one-year observational period [i.e., the change in LDL-C was—0.91 mg/dl (SD = 22.8), grams of CHO was 0.54 (SD = 80.4), and GI was 0.42 (SD = 8.0)]. Therefore, the associations between CHO and blood lipids from this study were mainly encountered in the cross-sectional (between-subject), and not in the longitudinal (within-subject) analyses. This is essentially the converse of what has been reported in large-scale intervention trials regarding the temporal relationship between total cholesterol and dietary fat intake, where relatively predictable changes in serum cholesterol values are observed with changes in dietary fat intake, but there is no observable difference cross-sectionally [43
We found that GL was associated with a decrease of total cholesterol and LDL-C cross-sectionally, and an increase of total cholesterol and LDL-C in the longitudinal analyses. Acute increases in carbohydrate consumption will increase blood insulin concentrations, thereby perhaps increasing total cholesterol and LDL-C production [38
]. However, chronic increases in GL intake (e.g., evident cross-sectionally) may decrease insulin sensitivity, thereby decreasing LDL-C production [44
HDL-C and LDL-C are the major focus in the US National Cholesterol Education Program guidelines [46
]. Our results showed an inverse relation between HDL-C and carbohydrate predictors. According to the Framingham Study, for each 1 mg/dl decrease in HDL-C CHD risk increases by ~3% in women and ~2% in men [48
]. Based on results from this study, a ten-unit increase in GI is associated with a decrease of 1.6 mg/dl in HDL, which in turn would translate into a 5.1% increase in CHD risk. Also, LDL-C and total cholesterol are important determinants of CHD. In general, a 10 mg/dl change in LDL-C is associated with a 5 to 7 percent change in CHD risk over 14 years, independent of the other major coronary risk factors [5
]. Our data indicated inverse relations of LDL-C and total cholesterol concentration with grams of carbohydrates and GL, therefore, grams of carbohydrate and GL may be associated with CHD, supporting results from Liu and colleagues [6
Claims regarding the effect of a low-carbohydrate diet or lowering GI or GL on blood lipids are premature. Some randomized controlled trials (RCTs) using a low-carbohydrate or a low GI diet have been done recently; however, interventions have been limited due to small sample size and short duration. For example, Sloth and colleagues found reduced LDL-C after 10 weeks of low GI diet in 23 healthy overweight women [49
]. While low carbohydrate intakes have been associated with lowering serum triacylglycerol levels, the effect on HDL-C and LDL-C levels is still controversial [50
]. The long-term impact of dietary CHO intake on CHD is even less clear; a recent meta-analysis of 15 RCTs for low GI diet indicated that no study reported an effect of low GI diet on CHD mortality or morbidity [40
]. Long-term intervention studies in diverse populations are needed to clarify the relationship between various carbohydrate factors, other aspects of diet, and physical activity in relation to lipid profiles and CHD.
There are several strengths to our investigation. Previously, GI and GL had been computed from food frequency questionnaires (FFQs) querying either the past month or previous year [12
]. The 24HR utilized in the present study provide more accurate data for computing GI and GL [53
]. Because they allow much greater specificity, the 24HR provide a better measure of factors related to the GI, including a great variety (i.e., tens of thousands) of foods, portion sizes, cooking, and other preparation methods. By contrast, FFQs must estimate nutrient intakes from a composite listing of only about a hundred foods, rely on a small number of comparisons (usually 3) with standard portion sizes, and they are generally self-administered (and thus do not allow for careful probing). By utilizing data pooled from three 24HR, the nutrient intake is a more stable point estimate approximating true intake than one 24HR. The current study also collected information on many possible confounding factors, including BMI, smoking, alcohol intake, and physical activity, which were controlled for in the analysis. Finally, two to five time point measures of dietary factors and lipid variables provided more reliable values for the analyses than a single measurement.
On the other hand, our study also has several potential limitations. Though the 24HR is the self-report method associated with the lower overall error compared with FFQ [54
], information on diet and physical activity was still obtained from self-report and this measurement is subject to information bias. Also, there is a potential limitation in generalizing our study results. Participants in this study included highly motivated men and women between the ages of 20 and 70 years, who were predominantly well-educated, employed full time, and white. In addition to issues around selection bias, the physiological mechanism underlying the relationship between carbohydrate intake and serum lipids may vary across race and ethnicity, which is suggested by the greater prevalence of metabolic syndrome and diabetes among African-American and Hispanic populations [58
]. Caution should be taken when generalizing to populations that have different baseline characteristics and/or dietary patterns with average carbohydrate intake values different from the range found in this study. The most consistent findings from this study derive from cross-sectional associations. As such, they are less likely to be considered “causal”.