In this prospective study of 26,330 initially healthy women, the concentrations of lipids and apolipoproteins differed minimally when measurements were performed on nonfasting compared with fasting blood, except for triglycerides which were higher when nonfasting. However, the associations with CVD were stronger for fasting compared with nonfasting measurements of total cholesterol, LDL cholesterol, apolipoprotein B100, non-HDL cholesterol, and the apolipoprotein B100/A-1 ratio. By contrast, the associations with CVD were similar for fasting and nonfasting HDL cholesterol, apolipoprotein A-1, and the total/HDL cholesterol ratio, and stronger for nonfasting triglycerides. These observations suggest that nonfasting blood draws may be highly effective and practical when limited to HDL cholesterol, total/HDL cholesterol ratio, and triglycerides. However, these data also suggest that a fasting sample is preferred if risk assessment is based on total cholesterol, LDL cholesterol, or non-HDL cholesterol.
Prior studies have found lower concentrations of LDL cholesterol postprandially, and higher triglycerides, with a similar magnitude of difference in our study compared with prior studies that used a typical non-high fat meal.6,15,16
Our finding that there was no significant difference between fasting and nonfasting measurements of HDL cholesterol and apolipoprotein A-1 is also consistent with other studies.17,18
However, to our knowledge, this is the first study that prospectively compares the association of a comprehensive panel of lipids and apolipoproteins with CVD depending on the time to last meal. While prior studies have evaluated the effect of food intake on lipid and apolipoprotein concentrations,6,16,17,19-22
the influence of postprandial time on the predictive value of lipids and apolipoproteins, other than triglycerides, is scarce. In a prior case-control report examining 683 postmenopausal healthy women that included some who were nonfasting, the results were not analyzed according to fasting status except for triglycerides, which showed similar prediction in the fasting or nonfasting state.23
The AMORIS study included a large proportion of women, with a third of participants who were nonfasting, but associations of lipids and apolipoproteins with fatal myocardial infarction were not examined according to fasting status.24
Other prospective studies that included a large number of nonfasting participants had data only on men and did not have comparisons with fasting lipids.25-27
Although differences between fasting and nonfasting concentrations of lipids and apolipoproteins, except for triglycerides, were small and clinically insignificant in our study, the strength of the association of various lipids and apolipoproteins with CVD differed by fasting/nonfasting status. Total cholesterol and LDL cholesterol showed the most marked differences in their predictive value, although different associations were also found for apolipoprotein B100, non-HDL cholesterol, and the apolipoprotein B100/A-1 ratio, all of which were stronger in the fasting state. This finding suggests that measuring a nonfasting measurement of total cholesterol or non-HDL cholesterol, which is currently believed to be acceptable, may need to be interpreted with caution.
As suggested by , even stronger associations may be observed within 6 to 8 hours postprandially for lipids and apolipoproteins that represent part of the atherogenic dyslipidemia of the metabolic syndrome, such as HDL cholesterol and triglycerides, while longer durations of fasting (>10 to 12 hours) may be required for total cholesterol and LDL cholesterol. The underlying biological explanation for this is unclear, but may relate to the time course of postprandial triglyceride metabolism, since 4 to 8 hours is the time of peak triglycerides, and by 8 hours, triglyceride concentrations have returned to fasting concentrations in most individuals.28
There are several limitations of the present study. Time to last meal was self-reported, and we did not have both fasting and nonfasting measurements in the same individuals. Lipid measurements were only available once at baseline and results could not be corrected for potential regression dilution bias. We only had data on women, although no substantial differences were noted in women who were or were not taking hormones. Our study included healthcare professionals who were mostly white, apparently healthy, and recruited from a variety of geographic locations across the US; thus, it is unclear if our results would be applicable to other ethnic populations or men. Our statistical power was less in nonfasting than in fasting women. Finally, this was a primary prevention population and further studies are needed before the data can be extended to secondary prevention populations that are frequently treated with lipid lowering medications.
Strengths of the present study include the large number of healthy women participants with comprehensive measurements of a panel of lipids and apolipoproteins, including the direct measurement of standard lipids. Additionally, detailed information on cardiovascular risk factors was available, allowing for the control for potential confounding by these factors, such as the time of day of blood draw and hormone use. Finally, previous studies have not examined the influence of fasting status on the predictive ability of various lipids and lipoproteins, other than triglycerides, all of which was possible in this study due to the large number of participants in subgroups divided by time since the last meal.
In summary, this study demonstrates that HDL cholesterol, triglycerides, total/HDL cholesterol ratio, and apolipoprotein A-1 predict CVD when measured nonfasting. By contrast, total, LDL, and non-HDL cholesterol, in addition to apolipoprotein B100 and B100/A-1 ratio, may provide less useful CVD risk information when measured nonfasting, despite small changes in their concentrations. Guidelines for lipid screening may need to consider these differences.