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© 2001 American Heart Association, Inc.
Atherosclerosis and Lipoproteins |
Metabolic and Lifestyle Determinants of Postprandial Lipemia Differ From Those of Fasting Triglycerides
The Atherosclerosis Risk in Communities (ARIC) Study
From the Epidemiology and Biometry Program (A.R.S., S.A.C), National Heart, Lung, and Blood Institute, Bethesda, Md; the Departments of Epidemiology (G.H.) and Biostatistics (L.E.C.), University of North Carolina School of Public Health, Chapel Hill; the Genetics Center (E.B.), University of Texas Health Science Center, Houston; the Division of Epidemiology (A.R.F.), School of Public Health, University of Minnesota, Minneapolis; and the Department of Laboratory Medicine (W.P.), Landeskrankenanstalten, Salzburg, Austria.
Correspondence to A. Richey Sharrett, MD, DrPH, Division of Epidemiology and Clinical Applications, Room 8164, MSC 7934, National Heart, Lung, and Blood Institute, 6701 Rockledge Dr, Bethesda, MD 20892-7934. E-mail Sharretr{at}nih.gov
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Abstract |
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Abstract—Despite the reported association of lipoprotein responses to a fatty meal with atherosclerosis, little is known about the determinants of these responses. Plasma triglyceride, retinyl palmitate, and apolipoprotein B-48 responses to a standardized fatty meal containing a vitamin A marker were measured in 602 Atherosclerosis Risk in Communities (ARIC) study participants. To focus on postprandial responses specifically, which have been reported to be related to atherosclerosis independently of fasting triglycerides, analyses for determinants of postprandial responses were adjusted for fasting triglycerides. Major determinants of fasting triglycerides, namely, diabetes, obesity, other factors related to insulin resistance, and male sex, were not independently associated with postprandial responses. Fasting triglycerides were the strongest predictor of postprandial lipids, but independent of triglycerides, the predictors of postprandial responses were smoking, diet, creatinine, and alcohol. Smokers had substantially increased retinyl palmitate and apolipoprotein B-48 responses, indicators of chylomicrons and their remnants. Persons who consume more calories or
3 fatty acids had
reduced chylomicron responses. Triglyceride responses were
associated positively with serum creatinine levels and
negatively with moderate alcohol consumption. Thus, determinants of
fasting and postprandial lipids differ. The independent atherogenic
influence of postprandial lipids may relate more to smoking and diet
than to obesity and insulin resistance.
Key Words: lipoproteins • postprandial • chylomicrons
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Introduction |
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Typical Western diets cause postprandial lipemia 18 hours per day, and this response is related to atherosclerosis1 2 and coronary heart disease.3 4 To date, however, there is little information on the metabolic or lifestyle characteristics associated with the lipemic response.
To investigate these associations, we studied participants of the largest published study of atherosclerosis and postprandial lipemia.1 The Atherosclerosis Risk in Communities (ARIC) postprandial lipemia study demonstrated in 602 men and women that asymptomatic carotid atherosclerosis was positively associated with postprandial triglycerides (TGs) independently of coronary risk factors and fasting TGs.1 Markers of intestinally derived postprandial lipoproteins were also studied, because small studies had previously reported coronary disease associated with the apoB-48/apoB-100 ratio3 and a retinyl palmitate (RP) marker of these lipoproteins.4 However, these markers were not associated with carotid atherosclerosis in the present study or a more recent study.2 Despite a lack of association with intestinally derived lipoproteins, our finding that atherosclerosis was associated with postprandial TGs independently of fasting TGs suggested that lipoprotein characteristics specific to the postprandial state are atherogenic. The large size of the ARIC study is needed to detect the independent determinants of postprandial responses, inasmuch as postprandial responses are closely correlated with fasting TGs: r=0.64 for TGs and 0.49 for RP in the ARIC study.
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Methods |
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Participants in the postprandial lipoproteins study were selected from the 15 792 participants in the ARIC study, who lived in communities in North Carolina, Maryland, Minnesota, or Mississippi, as cases of carotid atherosclerosis or as control subjects, with atherosclerosis defined on the basis of ultrasound measurements of carotid intima-media thickness. Cases had thickness values above the 95th percentile of the ARIC distribution (the criterion relaxed to the 90th percentile for blacks to obtain enough cases for study), and control subjects had thickness values below the 75th percentile in all artery segments evaluated. Participants were excluded if they reported any clinical manifestation of cardiovascular disease.
The postprandial study was performed at the first follow-up examination, 3 years after baseline, in 1990 to 1993, when participants were aged 48 to 67 years. A recruitment interview was used to exclude pregnant women and individuals with elevated fasting TGs (400 mg/dL), individuals with liver, kidney, pancreas, or gall bladder disease or malabsorption, and individuals who used insulin, hypoglycemic or lipid-lowering medications, thyroid medication, ß-blocking agents, or sex hormones.
Factors studied in relation to postprandial lipid response
were assessed at the examination that included the fat tolerance test.
Usual dietary intakes were estimated by use of a semiquantitative food
frequency questionnaire.5 Food
intake pattern was determined from responses to 2 questions: (1) How
many times do you usually eat in a day, including your snacks? (2) Of
all the food you eat in a day, how much do you usually eat at the
biggest meal: less than half, about half, or more than half? We defined
"gorging" as eating more than half at the biggest meal and
averaging 
3 meals a day and "nibbling" as eating at least 3 meals
a day and less than half at the biggest meal.
Physical activity at work, during leisure, and in sports was
assessed by a standard
questionnaire.6 Participants
were asked if they currently smoked cigarettes. Height, weight, and
waist and hip girths were measured, and body mass index (BMI), weight
(kilograms)/height (meters squared), and waist/hip ratio were
calculated. Participants were asked to recall their weight at age 25.
Diabetes was defined by criteria of the America Diabetes Association
(fasting glucose 
126 mg/dL). Alcohol questionnaire responses were
calculated as grams consumed per week.
Fat-Tolerance Test
The fat-tolerance test and lipid methods have been
described.1 Participants were
fasting and had abstained from exercise for 12 hours. The test meal,
consisting of whipping cream, ice cream, safflower oil, chocolate
syrup, powdered protein, and 100 000 IU vitamin A, contained 1265
kcal, 32 g protein, 48 g carbohydrate, and 105 g fat per
2 m2 of calculated body surface
area.7 After the test meal,
participants took nothing by mouth except water or unsweetened drinks
for 8 hours and abstained from exercise. Blood specimens were drawn at
3.5 and 8 hours. The limitation to only 2 postprandial blood
collections does not affect measurement precision. Our companion
study8 showed that
postprandial responses calculated from 4 postprandial measurements were
correlated (0.97) with responses calculated from only the 3.5- and
8-hour blood samples.
Postprandial blood specimens were centrifuged, stored in the dark under N2, and shipped on ice to the laboratory in Houston.
Laboratory Methods
Plasma total cholesterol, TGs, and HDL
cholesterol (HDLc), after magnesium dextran precipitation,
were measured enzymatically. LDL cholesterol levels were
calculated by the Friedewald method. TG-rich lipoproteins
(density<1.006) were isolated by ultracentrifugation,
and the apoB-48/apoB-100 ratio in the TG-rich lipoproteins was
determined by SDS
electrophoresis.9 Plasma RP
levels were determined by high-pressure liquid
chromatography.9
Fibrinogen was measured by thrombin-time titration10 ; insulin, by radioimmunoassay; and glucose, uric acid, and creatinine, by standard methods.
Statistical Methods
Postprandial responses were calculated as the
incremental area under the curve (AUC) defined by TG, RP, or apoB-48
levels at time 0 and at 3.5 and 8 hours after the test meal. Multiple
linear regression was used to examine AUC associations with independent
variables. Backward stepwise linear regression for each AUC
measurement was used to identify multivariate
independent variables. Natural logarithm transformation on AUC
variables was used to meet general linear model assumptions. Mean
values presented are geometric means. Because the regression
models use the logarithm of a specific lipid as the dependent
variable, the regression coefficient is an estimate of the
differences in the logarithm for a unit difference in the independent
variable. Because the difference in logarithms is the logarithm of
a ratio, the regression coefficient can be expressed in exponential
fashion (eß) to produce an estimate of the ratio of the dependent
variable as a function of a unit difference in the independent
variable. The percent difference that we cite in our tables is this
value minus 1 and multiplied by
100.
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Results |
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ARIC participants free of cardiovascular disease were invited for the study if they met carotid thickness criteria; there were 326 white and 185 black carotid thickness cases and 397 white and 206 black controls (Table 1
). Refusal rates were low, as were exclusions for
test-meal intolerance or failure to consume the full test meal. More
cases than controls were excluded for medical conditions. There were
602 participants in the study: 444 whites (170 cases and 274 controls)
and 158 blacks (59 cases and 99 controls).
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Postprandial responses and major independent variables
are shown in
Table 1
. Mean fasting TGs and postprandial TG, RP, and
apoB-48 responses were similar by race among control subjects, and the
small race differences seen were not significant. Among cases, however,
whites had higher fasting and postprandial TG levels, perhaps because
we accepted a less specific definition of cases in blacks than in
whites to increase the number of cases. For this reason, all
analyses were stratified by race and adjusted for case status,
sex, and age. Models including only these variables found no
case-sex interaction for either race.
Despite the fact that men and women had similar mean fasting TGs, men consistently had greater postprandial responses. The response in men exceeded that in women by 32% for whites (P<0.05) and 38% for blacks (P=0.06) for TGs, by 11% for whites (P=0.06) and 18% for blacks (P=0.08) for RP, and by 28% for whites (P=0.27) and 24% for blacks (P=0.57) for apoB-48. Age was significantly (positively) associated with postprandial responses only in whites for TGs (P<0.01) and RP (P<0.05).
Associations of 24 risk factors with TGs and with TG, RP,
and apoB-48 responses were examined individually, adjusting for age,
sex, and case
(Table 2). Sex–risk factor interactions were examined for
each risk factor in both blacks and whites for each postprandial end
point. Only 2 of 192 interactions tested were significant at
P<0.01
(Table 2). These unexpected interactions were attributed to
chance, so the sexes were pooled for analysis.
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Fasting TG levels were consistently associated with
obesity and other factors related to diabetes
(Table 2), with positive coefficients for the waist/hip
ratio, BMI, weight gain, diabetes, fasting insulin and glucose, and
uric acid. Associations with dietary and other habits were generally
weak. Ethanol was an exception; consumption of 100 g per week was
associated with a 43% higher fasting TG level in blacks compared with
consumption of <100 g per week.
Determinants of postprandial TG levels were similar to those
for fasting TG levels by univariate analyses
(Table 2). Obesity and other insulin-related factors were
generally associated with enhanced response. A 1 SD higher
creatinine level was associated with a 32% higher TG
response in blacks, and consumption of 100 g per week of ethanol was
associated with a 27% lower TG response in whites.
With exceptions for RP in whites, obesity and glucose
metabolism were not strongly or consistently
associated with RP or apoB-48 response. Current smoking was associated
with higher RP and apoB-48 responses in both ethnic groups, and for
apoB-48, the associations were substantial and statistically
significant. Lower apoB-48 response was associated with greater calorie
and 3 fatty acid intake and with leisure activity in both blacks and
whites.
Meal pattern (gorging versus nibbling), fibrinogen, usual unsaturated fat intake, previous smoking, and work activity were not significantly associated with any postprandial response in either ethnic group.
All variables significantly associated with postprandial
responses were considered for multivariate
analysis. The 33 white and 15 black participants with diabetes
were excluded to obtain a better understanding of the role of insulin.
Four other variables were dropped: glucose (because of the
interaction of the sex of the participants with the TG response) and
BMI and carbohydrate and protein intake (because of their high
correlations with other included variables). Twelve remained for
multivariate analysis: waist/hip ratio, weight
gain, insulin, uric acid, creatinine, consumption of
calories, consumption of saturated fat, consumption of 3 fatty
acids, smoking, ethanol, and sport and leisure activities. Six
step-down multivariate analyses were performed:
TG, RP, and apoB-48 responses for both ethnic groups. These began with
the 12 independent variables, plus fasting TGs, to permit focus on
independent postprandial responses, and 3 forced variables: age,
sex, and case status. The 2 final models for TG response, 1 for whites
and 1 for blacks, included age, sex, case status, and all variables
that remained independently significant in either ethnic group. The
same strategy was used for the 2 models for the RP response and the 2
models for the apoB-48 response. HDLc and apoE genotype were
then forced into the final models as control variables to determine
whether they altered the observed effects of the metabolic
and lifestyle determinants of postprandial response.
Fasting TG level was strongly associated with TG response,
with a 0.5 mmol/L higher fasting level associated with increments
of 45% in whites and 46% in blacks
(Table 3, model 1). TG response was independently associated
with creatinine in blacks (0.017 mmol/L with a 28%
higher response) and ethanol consumption in whites (100 g per week with
a 21% lower response). HDLc, added to this model, was not significant
and did not alter the associations for the other variables
(Table 3, model 2). ApoE genotypes 23 and 34
compared with apoE genotype 33 also showed no independent
association, and their inclusion in the model did not alter
associations for the other variables
(Table 3, model 3). Too few participants had other apoE
genotypes (22, 24, or 44) for evaluation.
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Fasting TG level was also strongly associated with RP
response, with increments of 31% and 34% per 0.5 mmol/L fasting
TGs for whites and blacks, respectively
(Table 4, model 1). Current smoking was independently
associated with a 16% greater RP response in whites and a 36% greater
response in blacks. HDLc did not contribute independently to prediction
(model 2). However, apoE-23 was associated with increased RP response,
by 18% in whites (P<0.05) and
22% in blacks, compared with apoE-33 (model 3). None of the
associations was changed by including HDLc or apoE
genotypes.
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The apoB-48 response was not related to fasting TGs but was
independently associated with current smoking, usual consumption of
calories, and percent of calories from 3 fatty acids
(Table 5, model 1). The strongest association was with
smoking: there was an 80% greater response compared with nonsmokers
for whites and a 224% greater response for blacks. Consumption of more
calories and of 3 fatty acids was associated with reduced apoB-48
responses: each 622 calories per day was associated with reductions of
23% in whites (P<0.05) and
34% in blacks (not significant), and each 0.14% of calories as 3
fatty acids was associated with reductions of 21% in whites
(P<0.05) and 31% in blacks
(not significant). HDLc was independently associated with a reduced
apoB-48 response, which was significant in whites (model 2). The
inclusion of HDLc did not alter the association for the other
covariates. ApoE genotype did not contribute further to
prediction (model 3).
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Age and sex, although not shown, were included as forced
covariates in
Tables 3, 4, and 5. In these multivariate
analyses, men showed significantly greater postprandial
responses than did women only for TGs in whites. Other sex associations
were small, inconsistent, and not statistically significant.
Age effects were also small and
inconsistent.
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Discussion |
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The aim of the present report was to examine the factors related specifically to the postprandial responses, which may be atherogenic, so adjustment for fasting TGs was required here as it was in our previous analysis of the associations of postprandial responses with atherosclerosis.1 Strong determinants of fasting TG levels, such as diabetes, obesity, and other factors associated with insulin resistance, were not independently related to postprandial TGs, nor was habitual physical activity. However, smoking, diet, creatinine, and ethanol were independently associated with postprandial responses.
Despite similar fasting TG levels, men, as reported,11 12 had greater postprandial responses than did women. However, the present study shows no consistent independent sex association after adjusting for TGs and significant metabolic and lifestyle determinants.
Cigarette smokers had substantially greater postprandial RP and apoB-48 responses than did nonsmokers, despite the lack of an association with fasting or postprandial TGs. Our null fasting TG results appear inconsistent with a review13 and more recent reports,14 15 which show higher fasting TG in smokers, but only 1 study provided data on subjects as old as those in the ARIC study. Jenkins et al16 showed only a 2% higher fasting TG level in smokers than in nonsmokers among 924 men aged 50 to 59 years, in contrast to a 12% higher fasting TG level in younger smokers. Postprandial TG level was evaluated in 2 small studies: (1) Axelson et al17 showed 50% greater TG response in habitual smokers. (2) Mero et al18 showed that smoking raised retinyl esters and apoB-48, but not apoB-100. The ARIC study extends that finding to a large sample of men and women and supports the interpretation of Axelson et al that smoking affects TG metabolism primarily by raising lipoproteins of intestinal origin.
Despite the limitations of questionnaire assessment, 2
dietary variables were independently associated with postprandial
apoB-48 response in the present study. Total caloric and 3 fatty
acid intakes were associated with 20% to 30% reductions in the
apoB-48 response. The 3 fatty acid result is consistent with
a recent review.19 The
present finding that attenuation was confined to the apoB-48
response and was not found for TG or RP responses has not been reported
previously. The association of usual total caloric intake with reduced
chylomicron response to a high-calorie meal might represent an
adaptive response; however, we and
others20 did not find any
postprandial measure to be related to gorging versus
nibbling.
Serum creatinine was independently associated with elevated postprandial TG levels in blacks and with RP in whites. A previous ARIC publication showed fasting TGs to be associated with a subsequent rise in serum creatinine, and the authors suggested that lipids may contribute to glomerulosclerosis.21 Whether that would explain the associations found in the present study or whether a subclinical renal disorder contributes to an alteration in TG metabolism cannot be determined from available data.
The ethanol associations reported in the present study
do not fit a simple pattern. No associations were seen for light
drinking, but consumption of 100 g per week was associated with
greater fasting but not postprandial TG levels in blacks. In whites,
however, ethanol was not associated with fasting TG levels, but it was
associated with a 21% lower postprandial TG level, independent of
fasting TGs. No significant ethanol associations were seen for RP or
apoB-48 responses. Although habitual heavy
drinking22 is clearly
associated with elevated fasting TGs, studies of moderate consumption
usually find no
association.22 23
We have no explanation for the increased fasting TG levels in blacks.
Only 14 blacks consumed 100 g of ethanol per week, and their
consumption (239 g/wk) was similar to that of whites (223 g). Alcohol
consumed with an evening meal raises TG levels
acutely,24 25 as
well as RP,25 but no studies
to date have evaluated the nonacute postprandial effects of habitual
consumption. Because alcohol appears to increase both the
production and catabolism of VLDL
TGs,26 neither the decreased
postprandial TG levels in whites nor the lack of association with
postprandial TG in blacks is surprising. Further comment on the ethnic
differences seen in the present study would be only speculative,
inasmuch as they are based on such a small number of black
drinkers.
Diabetes, obesity, and elevated levels of fasting insulin, glucose, and uric acid were consistently related to fasting TG levels and (more consistently in whites than blacks) to TG postprandial responses as well. These associations with fasting TGs are well known, inasmuch as an elevated TG level is a recognized component of an insulin resistance syndrome that includes these variables,27 and these associations have been reported by use of data from the entire ARIC population.28 However, in the present study, we found that none of the insulin-related variables was independently associated with postprandial TG, RP, or apoB-48 responses in nondiabetics after controlling for fasting TGs. Smaller studies have reported associations of diabetes with TG response,29 associations of fasting insulin, BMI, and waist/hip ratio with TG response in nondiabetics,30 and associations of directly measured insulin resistance with both TG and RP responses,31 but no study has examined independent associations with postprandial responses after accounting for their strong associations with fasting TG levels. The ARIC results suggests that the influence of diabetes and the insulin resistance variables on TG metabolism does not preferentially involve postprandial lipids.
Habitual physical activity was not an important determinant of postprandial responses in the present study. In univariate analyses, sport and leisure activities were associated with reduced RP and apoB-48 AUC in whites, but no activity measures were associated with postprandial responses after adjusting for fasting TGs. Yet endurance training is clearly associated with reduced responses measured within a day or 2 of the last bout of vigorous exercise.32 33 However, this effect is lost 60 hours after exercise,34 35 and perhaps few of the ARIC participants, aged 48 to 67 years, had performed vigorous activity within 60 hours of the postprandial test. Participants were activity-restricted during the test.
We showed previously that the apoE polymorphism affected
postprandial RP but not TG responses in the ARIC
study.9 We extend the finding
to the present study by showing that apoE-23 was associated with an
20% greater RP response compared with apoE-33, even after adjusting
for other important determinants, namely, fasting TG levels, smoking,
and creatinine levels.
Although the present study is large and applicable to both men and women, it is limited in the precision with which questionnaire variables such as exercise and diet are measured. Extraneous variables are not controlled as they would be in an experiment. The study sample selected includes a disproportionate representation of persons with greater carotid artery thickness, and this may limit its generality. However, exclusion of participants with any evidence of cardiovascular disease reduces the likelihood that results are confounded by any changes in lifestyle or medications resulting from overt disease.
In summary, we find that major determinants of fasting TG
levels, namely, diabetes, obesity, other components of the insulin
resistance syndrome, and male sex, are not independent predictors of
postprandial responses. Responses of intestinally derived lipoproteins
are substantially increased in current smokers and are reduced in
persons who habitually consume more 3 fatty acids or total calories.
Less consistently, TG responses are associated positively with
creatinine levels and negatively with moderate ethanol
consumption. These factors, rather than those related to insulin and
obesity, deserve more attention in relation to the specific
atherogenicity of postprandial
lipoproteins.
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Acknowledgments |
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This research was supported by grant No. U01 HL-45467 and contracts N01-HC-5-5015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, and N01-HC-55022 from the National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda Md. Authors thank the ARIC staff and participants for their important contributions.
Received May 31, 2000; accepted November 6, 2000.
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