Denke MA, Adams-Huet B, Nguyen AT. Individual Cholesterol Variation in Response to a Margarine- or Butter-Based DietA Study in Families. JAMA. 2000;284(21):2740-2747. doi:10.1001/jama.284.21.2740
Author Affiliations: Department of Internal Medicine (Dr Denke and Ms Adams-Huet) and Center for Human Nutrition (Dr Denke and Ms Nguyen), University of Texas Southwestern Medical Center, Dallas.
Context The effectiveness of dietary modification in reducing low-density lipoprotein
cholesterol (LDL-C) levels can be reliably predicted for populations, but
not for individuals.
Objective To determine whether individual variation in cholesterol response to
dietary modification is a familial trait.
Design Two-period, outpatient crossover trial conducted from September 1997
to September 1999.
Setting and Participants Fifty-six families from the Dallas–Ft Worth, Tex, area with 2
biological parents and at least 2 children aged 5 years or older volunteered;
46 families (n = 92 adults and n = 134 children) completed the study.
Intervention All families followed two 5-week dietary regimens that included individualized
daily dietary prescriptions and emphasized a low–saturated fat diet
supplemented with specially manufactured baked goods and spreadable fat. One
regimen used butter only and the other used margarine only.
Main Outcome Measure Mean LDL-C levels during the last 2 weeks of each dietary period.
Results Margarine intake compared with butter intake lowered LDL-C levels 11%
in adults (95% confidence interval [CI], 13% to 9%) and 9% in children (95%
CI, 12% to 6%) (P<.001 for both adults and children).
The distribution of individual responses were peaked around the mean response.
For adults and children together, family membership accounted for 19% of variability
in response (P = .007). In children, family membership
accounted for 40% of variability in response of percent change in LDL-C levels
(P = .002). Body mass index and change in cholesterol
ester (CE) 18:2/18:1 ratio accounted for 26% of variation, leaving 26% still
attributable to family membership. In all participants, BMI predicted response—heavier
individuals had higher LDL-C levels, less excursion in CE fatty acids, and
less LDL-C response to dietary change.
Conclusions Our results suggest that individual variation in response to a cholesterol-lowering
diet is a familial trait. Body weight is an important modifiable factor that
Cholesterol-lowering diets have been recommended for the population
at large to reduce the incidence of coronary heart disease.1
Changes in the mean lipid2,3 and
lipoprotein4,5 levels can be reliably
predicted from changes in population intake of dietary fatty acids and cholesterol.
The projected benefits of dietary modification are substantial and are directly
linked to the magnitude of cholesterol level reduction.6
Although populational responses to diet can be reliably predicted, it
is impossible to predict how much cholesterol lowering a given individual
will achieve as a result of dietary modification. Individual responses follow
a peaked distribution around the mean population response. Theoretically,
two thirds of individuals fall within 1 SD of the mean response, with some
individuals having little or no cholesterol-lowering response to diet.7,8
Predicting who will and will not respond to diet modification would
allow the clinician to target aggressive cholesterol-lowering dietary therapy
for those patients who are most responsive to diet. It also would allow the
clinician to differentiate between nonresponders who are noncompliant from
nonresponders who do not have the biological potential to respond to diet
This study was designed to evaluate whether familial differences explain
why individuals respond differently to cholesterol-lowering diets. The prevalence
of individuals who do not respond to diet has been estimated at 17% of institutionalized
men on a controlled diet9 and 15% to 20% of
free-living men,9- 11
women,12 and children13
on counseled diets. Although associations between specific genotypes and dietary
responsiveness among unrelated individuals have been reported, no factor has
been found to be consistently associated with response, and no single factor
has explained more than 10% of the individual variation observed.
The study protocol was approved by the institutional review board at
the University of Texas Southwestern Medical Center and the Human Subjects
Review Committee at the Veterans Health Administration North Texas Center,
Families from the Dallas–Ft Worth metroplex were recruited during
their attendance at various museums, health fairs, and church events over
2 years (September 1997 to September 1999). Families were selected by 2 criteria
only: interest in participation and having an intact family with 2 biological
parents and 2 or more biologically related children aged 5 years and older.
During a follow-up telephone contact, a home visit was scheduled where the
study was described, and the age, height, weight, physical activity, and dietary
preferences for all family members were recorded. If all family members remained
interested, a date was set to draw ad libitum fasting blood samples and study
initiation. Fifty-six families agreed to participate, and 46 families completed
the entire diet study. Reasons for dropout included difficulty following dietary
protocol restrictions (5 families), refusal of a child to have blood drawn
after the study was initiated (2 families), and change in health status of
parent (3 families). Of the 46 families, 39 were white, 3 African American,
2 Hispanic American, 1 American Indian, and 1 Asian American. Baseline characteristics
of the 46 families are detailed in Table
1; the characteristics of the 10 families who dropped out were similar
to those who completed the trial. All children completing the trial received
a $50 payment. All family members completing a 3-day diet record received
1 movie pass (value $4) for each of the 4 requested records.
The study was a 2-period, crossover, outpatient diet counseling study
designed to compare the isocaloric substitution of butter for margarine as
the major dietary fat intake. Each dietary period was 5 weeks in duration.
Since commercial tub margarine is 60% or less fat by weight and butter is
80% fat by weight, a single batch of 80% fat by weight margarine was produced
for this study (courtesy of Unilever, Baltimore, Md). This allowed for a 1-to-1
substitution of the fats for use as a spread as well as in cooking and baking.
The margarine contained 38.7% cis-polyunsaturated
fatty acids and 7.5% trans-fatty acids. The butter
contained 50.6% saturated fatty acids, of which 8.6% was stearic acid.
Specially formulated products were produced by a local bakery for use
in the study. Participants/assessors could not be blinded to the type of fat
because of the inherent differences in study products (eg, margarine tub vs
butter pat). To avoid accidental substitution of butter fat for margarine
fat in cookies and brownies, the bakery was contracted to produce only 1 test
product line at a time. Every 3 months, production was temporarily halted
and switched to the other product line, making the entry date into the study
the criterion that assigned diet order. Twenty-three families (n = 104) had
diet order butter-margarine, and 23 families (n = 122) had diet order margarine-butter.
The 2 diet periods were separated by at least a 1 month of ad libitum diet;
families whose participation spanned the Thanksgiving-Christmas-New Year holiday
had a 3-month hiatus between diet periods to avoid problems fitting traditional
holiday foods into the dietary regimen.
Based on age, height, weight, physical activity profile, and food preferences,
each family member received a written dietary prescription specifying the
portion size and frequency of study foods, meat, starchy vegetable, regular
vegetable, fruit, and dairy to be consumed every day. Dietary prescriptions
were adjusted as needed during the first few weeks of each diet period to
maintain a constant weight in study participants.
The daily prescription was based on an intake of 25% of energy from
test fat. Subjects were instructed to follow the plan as much as possible
and to choose low-fat foods for their nonstudy food choices. We expected an
inability to adhere to the protocol for 3 meals each week, with a projected
test fat intake of 21% of calories. Families were counseled to continue a
low–saturated fat diet during their meals that did not contain study
products. A portable food scale was provided and household cups and bowls
were used to instruct families on how to estimate portion size.
Compliance to diet was assessed by 3 measures:
Product Inventory for Family. During each weekly visit, sufficient study products were delivered to
families by investigators to meet 100% adherence to the daily dietary prescription.
During the delivery, an inventory of unconsumed food products was recorded.
Allowing for 3 meals per week without study foods, 85% of the delivered food
was expected to be consumed.
Daily Check Sheets. All family members were provided personalized daily check sheets to
mark off how much of each study product they consumed each day. Sheets were
collected during the weekly visit and recorded, and the grams of test fat
consumed were calculated. Adherence was estimated as gram intake reported
to be consumed divided by gram intake for 100% adherence. As with family inventory,
the goal intake was 85%.
Three-Day Diet Records. During the third and fourth week of each diet period, each subject was
asked to complete a 3-day diet record of total dietary intake during a weekend
day and 2 weekdays. Records were analyzed using Nutritionist IV (San Bruno,
Calif), and the gram intake of test fat was calculated. Goal intake of test
fat was 21% of total energy.
Subjects had blood drawn prior to initiation of the study (ad libitum)
and twice during the last 2 weeks of each dietary period. Blood samples were
drawn 4 to 7 days apart to minimize the influence of biological variation
on mean response.14 All blood samples were
obtained after having subjects fast for 10 hours; all blood samples were stored
using numeric identification code that could be decoded only by the investigators.
Lipoprotein Analysis. Lipid and lipoprotein analyses were performed on each blood sample.
Plasma was separated, and plasma concentrations of total cholesterol (Roche,
Indianapolis, Ind) and triglycerides (Sigma Diagnostics, St Louis, Mo) were
measured using an enzymatic procedure. High-density lipoprotein cholesterol
(HDL-C) level was measured as the remaining cholesterol in whole plasma after
precipitating apolipoprotein B–containing lipoproteins with 6.59 mmol/L
of phosphotungstic acid (Dade International, Miami, Fla). To reduce phlebotomy
requirements, the LDL-C level was calculated using the Friedewald equation.
If a subject had a fasting triglyceride levels greater than 4.52 mmol/L (400
mg/dL), the LDL-C levels were determined by direct assay (Sigma Diagnostics).
Dietary Response. Response to diet was defined as the difference in mean LDL-C level of
the margarine intake period minus the mean LDL-C level of the butter intake
Cholesterol Ester and Triglyceride Fatty Acids. Plasma triglyceride and cholesterol ester (CE) fatty acids levels were
determined in the last blood draw of each diet period by extracting lipids
from plasma15 and separating lipid classes
by thin-layer chromatography.16
Genotypes for Apolipoprotein E (ApoE) and 7 α-Hydroxylase. DNA was extracted from the white blood cell pellet with DNA-zol Reagent
(GIBCO-BRL, Grand Island, NY). 7 α-Hydroxylase DNA was amplified with
1 pmol/µL of each primer AP2 (5′-TGGTAGGTAAATTATTAATAGATGT-3′)
and AE (5′-AAATTAAATGGATGAATCAAAGAGC-3′).17
The polymerase chain reaction (PCR)–amplified DNA fragment was digested
with 10 units of BsaI and was electrophoresed. Apolipoprotein
E DNA was amplified by PCR in a DNA thermal cycler using oligonucleotide primers
F4 (5′-ACAGAATTCGCCCCGGCCTGGTACAC-3′) and F6 (5′-TAAGCTTGGCACGGCTGTCCAA-GGA-3′).18
To evaluate the reproducibility of individual dietary response, each
of the first 20 families that completed the study were asked at the time of
their sign-out interview to consider repeating the entire diet study. Two
families agreed (n = 4 adults and n = 8 children). The first family began
the second dietary trial 5 months later and received the study foods in the
same diet order as their original study. The second family repeated the study
3 months later, receiving the opposite diet order. Body mass index (BMI; calculated
as weight in kilograms divided by the square of height in meters) measurements
prior to each study were fairly comparable except in 2 members of the first
family who gained 9 kg (20 lb) during the interval between their dietary trials.
The primary analysis was dietary response, which by definition could
be determined only in those families who completed the trial. To avoid underestimating
SEs because of correlations between family members, generalized estimating
equations (GEEs) were used to compare the 2 diets and construct confidence
intervals (CIs) to adjust for the lack of independence within families.19 Triglycerides levels were log transformed because
of skewness; both untransformed and transformed data gave similar results
so only untransformed data are reported. Also, GEE was used to assess the
reproducibility among the 2 families who agreed to repeat the study.
Mixed linear models were used to assess covariates and variance components.20,21 In these models, family membership
was included as a random effect. Bakery run or diet order did not contribute
to observed variance. Individual level covariates considered for the model
were either clinically relevant or significantly associated with dietary response
by univariate analysis. These covariates included age, BMI, ad libitum LDL
levels, ApoE genotype, and change in serum fatty acid CE levels. Because of
significant interrelationships among these covariates, all possible interactions
between these covariates also were considered. Apolipoprotein E genotype was
evaluated by combining several genotypes into 3 categories: ApoE 2,2 plus
2,3; ApoE 3,3 plus 2,4; and ApoE 3,4 plus 4,4. Comparison of these 3 categories
was made using 2 dummy variables in the models. Variance components were used
to estimate family intraclass correlation. Separate regressions also were
estimated for adults and children. One extreme outlier, a child with a dietary
response of –109 mg/dL (−2.8 mmol/L), was not included in regression
Statistical analysis was performed using SAS version 8.0 (SAS Institute,
Cary, NC). Because of the multiple testing, a P<.01
was assigned as significant.
By all measures, compliance to the dietary protocol was excellent. According
to food inventory, families consumed a mean (SD) of 88% (12%) and 83% (16%)
of test fat delivered during the margarine or butter intake periods, respectively.
Daily check sheets showed consistently lower mean (SD) intakes of 75% (18%)
and 77% (17%), respectively. The consistently lower intakes of test fat recorded
on daily check sheets may reflect some days in which subjects consumed test
fat but did not record their consumption.
The mean intake of macronutrients recorded on the 3-day food records
is listed in Table 2.The goal
of test fat intake of 21% of energy was achieved for the margarine intake
period but was significantly lower for the butter intake period (18% of calories, P < .01). The lower intake of test fat in the butter
intake period was accounted for by an unanticipated preference for the margarine
bread compared with the butter croissants. The 3% less energy from test fat
during the butter intake period was offset by small increases in calories
from protein (P<.01) and saturated fat (P<.01) from other sources (eg, whole milk and ice cream).
Dietary cholesterol was significantly higher (P<.01)
for the butter intake period. The overall dietary goal—to achieve a
clinically significant difference in intake of cholesterol-raising fatty acids
for the 2 diets—was achieved.
Consistent with the reported intake, there was no change in body weight
between the 2 diet periods (Table 3).
Margarine intake produced significantly lower total LDL-C levels than butter
intake (P<.001). Adults were more responsive than
children on the basis of levels (0.41 mmol/L [16 mg/dL] vs 0.28 mmol/L [11
mg/dL], P = .03) but not when considered as percent
reduction of LDL-C levels (11%; 95% CI, 13% to 9% mg/dL vs 9%, 95% CI, 12%
to 6%; P = .17).
No significant differences in HDL-C levels were seen in adults (P = .83) and children (P = .80).
A trend for an increase in triglycerides during the butter intake period was
seen in adults (P = .03) but not in children (P = .45).
Changes in CE fatty acids mirrored changes in dietary intake, with significant
increases in CE 18:2 content and decreases in CE 16:0 content in the margarine
intake period compared with the butter intake period (P<.005). The primary change in CE content was a substitution for
the CE 18:1 content by CE 18:2 content during the margarine intake period,
which expressed as a ratio fell from percent (SD) of 5.7% (0.9%) in the margarine
intake period to 4.9% (0.8%) in the butter intake period (P<.001).
Dietary responsiveness was defined as the mean margarine LDL-C level
minus the mean butter LDL-C level. This value was expressed as either an absolute
value (mmol/L [mg/dL]) or percentage change from the LDL-C value achieved
in the margarine intake period.
Individual Variation in Dietary Responsiveness. The frequency distribution of individual responses to diet shows that
81% of subjects had lower LDL-C levels in the margarine intake period compared
with the butter intake period, and 76% had a 3% or greater reduction in LDL
levels (Figure 1).
Reproducibility of Individual Variation in Dietary Responsiveness. Two families (family 1 and family 2) repeated the diet study and 2 members
of family 1 gained 9 kg (20 lb) between dietary challenges. Mean LDL-C levels
and the ratio of CE 18:2/18:1 content obtained in the initial butter or margarine
intake period were compared with those values obtained in the repeat period.
The mean difference in change in LDL-C levels between the 2 trials was 0.01
mmol/L (0.5 mg/dL) (P = .78; 95% CI, 0.08 mmol/L
(−3.3 mg/dL] to 0.11 mmol/L [4.4 mg/dL]). Results were fairly reproducible
with low responders in the initial period having low response in the repeat
period and vice versa; those subjects who gained weight were less responsive
in the second dietary challenge, but their overall response remained in the
same rank order.
Self-reported paternity/maternity status was verified with ApoE and
7 α-hydroxylase genotypes expected/observed in the children compared
with their parents. Estimates for proportion of variance explained by family
membership were made using mixed linear models. Considering adults and children
in the same model, family membership accounted for 19% of variability in percent
change LDL-C levels (P = .007). When children were
considered separately (Table 4),
40% of the variability in percent change in LDL-C levels was explained by
family membership (P = .002).
No significant correlations were observed between variations in compliance
(estimated by family inventory, daily check sheet, and food record) and variation
in response to diet. No significant correlations were found between dietary
responsiveness and changes in body weight, diet order, age, 7 α-hydroxylase
genotype, or sex. Significant associations were found between dietary responsiveness
and BMI, ad libitum LDL-C levels, ApoE genotype, CE 18:2 content, CE 18:1
content, and changes in CE 18:2/18:1 ratio. These variables, in turn, were
significantly intercorrelated, making it difficult to quantify how much each
factor influenced response. Separate prediction models for adults (not genetically
related) and children (2-9 per family genetically related) were as follows:
Among children, family membership explained 42% of the variation in percentage
change in LDL-C levels (P = .002) (Table 4). Significant covariates of response were BMI and change
in CE ratio, explaining 26% of variation and leaving 26% still attributable
to family membership. The importance of BMI was even more striking considering
the relative leanness of the children compared with the adults. Among adults,
family membership accounted for 0% of variation in percentage change LDL-C
levels; BMI, ApoE genotype, and a BMI × ApoE interaction accounted for
14% of the variation observed.
The interrelationship between ad libitum LDL-C levels (a significant
predictor in children) and ApoE genotype (a significant predictor in adults),
the relationship between ApoE genotype, ad libitum LDL-C levels, and percentage
change in LDL-C levels were further evaluated. The ApoE genotype was significantly
associated with ad libitum LDL-C levels when comparing either ApoE 2,2 plus
3,2 vs 4,4 plus 4,3 or ApoE 3,3 plus 2,4 vs 4,4 plus 4,3 (both P = .002). However, ApoE genotype accounted for only 4% of the variation
in ad libitum LDL-C levels. Although ApoE genotype contributed more than ad
libitum LDL-C levels to dietary response in adults, in children the model
including ad libitum LDL-C levels accounted for 7% additional variance than
the model including ApoE genotype (data not shown).
Since BMI was the only factor consistently appearing in all models,
the relationship between BMI and response was examined further. Compliance
to diet was not associated with BMI, and differences in compliance were not
seen across categories of BMI (data not shown). Surprisingly, the change in
CE ratio paralleled the change in LDL-C levels; obese persons had approximately
half the response in LDL-C levels and CE ratio than leaner persons (mean [SD]
change in LDL-C levels and change in CE 18:2/18:1 ratio for BMI<21, 13
 and 0.85 [0.82], and for BMI ≥30, 9  and 0.42 [0.75]).
The substitution of margarine for butter creates 3 simultaneous changes
in dietary intake that, in turn, alter total cholesterol and LDL-C levels.22 Two changes—reductions in saturated fatty acids
and dietary cholesterol intake—lower LDL-C levels. A third change—increases
in trans-fatty acid intake—raises LDL-C levels
and also may lower HDL-C levels.23 Increases
in trans-fatty acid intake could potentially mitigate
the benefits of a margarine-based diet.24 In
our study, a low trans margarine-based diet achieved
11% lower LDL-C levels than a butter-based diet, without differences in HDL-C
levels. Our findings agree with those from metabolic diet studies evaluating
greater25 and lesser26
percentages of energy from butter vs margarine, confirming the long-standing
advice to the public at large to choose a tub margarine over butter. 27
Translating the public benefits of dietary modification to a given individual
are difficult because of individual variation in response to dietary change.
As previously reported, we found the distribution of dietary response to peak
around the mean: 19% of individuals had either no change or a paradoxical
increase in LDL-C levels in the margarine intake period compared with the
butter intake period. The differences in responsiveness to diet could be attributable
to genetic factors.28 In our study, we tested
this hypothesis by evaluating how individual family members responded to both
a cholesterol-lowering and cholesterol-raising diet. Family dietary responsiveness
data allowed for an estimation of the contribution of family membership (shared
genes plus shared environment) on responsiveness. A margarine vs butter comparison
was chosen since these 2 types of fats lend themselves to simple substitution
in both baking and spreads, and previous studies suggested that the response
to dietary cholesterol and saturated fat appear congruent.29
Ideally, a study of dietary responsiveness would be conducted under
more strict metabolic control to ensure standard intake of fats. For the number
of subjects in our study, a metabolic diet study would have been unwieldy
and costly. Using resources available, we taught families how to measure portion
sizes at home and provided detailed low-fat dietary prescriptions for each
family member. This base diet was supplemented with baked goods and spreadable
fats that were provided to the families. Subjects were given an explicit daily
and weekly goal for consumption of test fat and test fat products, and this
goal and their progress was reviewed during a weekly home visit. Compliance
was excellent, and the lipid lowering that was achieved matched that of the
predicted data derived from other metabolic diet studies.
The primary literature linking genetic factors with dietary responsiveness
in humans are reports from studies in unrelated individuals in which the genetic
analysis occurred after the dietary trial was completed.30
One study in which subjects were preselected based on their genotype, the
Apo A-IV allele was associated with variation in response to dietary cholesterol.31 Our study approached the issue of variability in
dietary responsiveness from a different angle: we evaluated dietary responsiveness
in families who shared lifestyle and dietary habits as well as genetic background.
ApoE and 7 α-hydroxylase are excellent candidate genes for dietary
responsiveness, since both influence LDL-C levels,17,32
and dietary responsiveness is known to be influenced by baseline LDL-C levels.33 We did not find a significant association between
7 α-hydroxylase genotype and dietary responsiveness, but we did observe
a small effect for ApoE genotype on the dietary response in adults but not
in children. Our failure to confirm an association between ApoE genotype and
responsiveness in children may be because of inadequate power or age differences
in the expression of ApoE, since not all studies in children have found an
ApoE influence on ad libitum LDL-C cholesterol levels34- 36
Similar to studies finding an association between ApoE genotype and response,
only 5% to 10% of variance could be attributed to ApoE variation.30
The observation that obese persons are less responsive to diet modification
adds to a growing literature linking body weight to lipids and to dietary
response. The linear and positive relationship between body weight and LDL-C
levels is present in younger persons but appears blunted by age.37,38
In children with familial hypercholesterolemia, body fat is a significant
predictor of ad libitum LDL-C levels.36 Thus,
it should not be surprising that body weight, like ApoE genotype, is an excellent
candidate factor for predicting responsiveness. Several studies have observed
that obese women compared with lean women are less responsive to a cholesterol-lowering
diet.39,40 One study found no
difference in response between obese and nonobese men,41
but another observed that nonobese, overweight men achieved only half of the
LDL-C level reduction by diet achieved by lean men.41
Our findings confirm and extend the notion that body weight predicts dietary
responsiveness in children as well as adults and for body weight differences
even among those who are lean. Excess body weight has no age or sex bias—people
who are overweight achieve less of a cholesterol reduction by diet than people
who are lean.
We measured CE fatty acids as a biological marker of adherence.42,43 In our study, the 18:2 content of
the margarine diet was far greater than that of the butter diet. The expected
increase in the CE content of 18:2 was observed, confirming adherence. Besides
a marker of adherence, we did not anticipate the contribution that other factors
make in determining CE content. The CE fatty acid content varies within a
relatively narrow range,44 does not predict
serum cholesterol levels,45 and may be subject
to genetic regulation. In a study of 69 twin pairs and their brothers, monozygotic
twins had smaller differences in CE fatty acid content compared with dizygotic
twins and brothers.46 Body weight can alter
CE fatty acid content. In the Atherosclerosis Risk in Communities study, even
after stratifying for dietary intakes, the CE saturated fatty acid levels
were higher and the CE content 18:2 was lower in overweight men and women
than lean men and women.47
When all subjects are stratified by categories of BMI, clear differences
in the change in CE fatty acid levels by diet were observed. Although a relative
increase in CE 18:2 content in the margarine intake period was seen in every
category of BMI, obese and overweight persons had less excursion in the CE
fatty acid levels during dietary modification than more lean persons. The
strong interrelationships between dietary responsiveness, CE ratio, and BMI
raise the hypothesis that the influence of dietary fatty acids on serum cholesterol
levels is tempered by the pool of endogenous fatty acids held in adipose tissue.
If relatively fixed concentrations of fatty acids in adipose tissue48 mix with dietary fatty acids and compete for hepatic
uptake, even on a low saturated fatty acid diet an obese person's liver is
exposed to more saturated fatty acid flux than a lean person's liver. One
can only speculate whether differences in fatty acid flux can explain the
observations that obese persons are less responsive to diet and have higher
cholesterol levels than lean persons.
The unimodal distribution of dietary responses observed in our study
are consistent with our failure to identify a single genetic factor that accounts
for variation in dietary response. By studying families, we could determine
that 40% of the variability in response to a cholesterol-lowering diet is
due to shared traits, whether these are heritable or habitual. Furthermore,
our study underscores the nearly universal response to a cholesterol-lowering
diet in both children and adults. This finding confirms the long standing
recommendation promoting a cholesterol-lowering diet for the population at