BMI indicates body mass index, calculated as weight in kilograms divided
by the square of height in meters.
Possible range of self-rated adherence level was from 1 (none) to 10
(perfect). Baseline values were carried forward in cases of missing data.
Range of standard deviation for all 4 diet groups was from 1.9 to 3.5.
Baseline values were carried forward in cases of missing data. The curve
in the weight change by diet type plot indicates the Lowess regression function,
a locally weighted, least-squares method using 3 iterations to fit the data.
The curves in the weight change by dietary adherence plot indicate the quadratic
regression functions for each diet group.
Baseline values were carried forward in cases of missing data. HDL indicates high-density lipoprotein. The curves in
all 3 plots indicate the linear regression functions for each diet group.
For difference between diet groups, P = .48 for total/HDL
cholesterol ratio; P = .57 for C-reactive protein;
and P = .31 for insulin level.
Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, Weight Watchers, and Zone Diets for Weight Loss and Heart Disease Risk ReductionA Randomized Trial. JAMA. 2005;293(1):43–53. doi:10.1001/jama.293.1.43
Author Affiliations: Division of Endocrinology,
Diabetes, and Metabolism (Drs Dansinger and Schaefer), and Institute for Clinical
Research and Health Policy Studies (Drs Griffith and Selker), Tufts-New England
Medical Center; and Lipid Metabolism Laboratory, Jean Mayer US Department
of Agriculture Human Nutrition Research Center on Aging, Tufts University
(Dr Schaefer and Ms Gleason), Boston, Mass.
Context The scarcity of data addressing the health effects of popular diets
is an important public health concern, especially since patients and physicians
are interested in using popular diets as individualized eating strategies
for disease prevention.
Objective To assess adherence rates and the effectiveness of 4 popular diets (Atkins,
Zone, Weight Watchers, and Ornish) for weight loss and cardiac risk factor
Design, Setting, and Participants A single-center randomized trial at an academic medical center in Boston,
Mass, of overweight or obese (body mass index: mean, 35; range, 27-42) adults
aged 22 to 72 years with known hypertension, dyslipidemia, or fasting hyperglycemia.
Participants were enrolled starting July 18, 2000, and randomized to 4 popular
diet groups until January 24, 2002.
Intervention A total of 160 participants were randomly assigned to either Atkins
(carbohydrate restriction, n=40), Zone (macronutrient balance, n=40), Weight
Watchers (calorie restriction, n=40), or Ornish (fat restriction, n=40) diet
groups. After 2 months of maximum effort, participants selected their own
levels of dietary adherence.
Main Outcome Measures One-year changes in baseline weight and cardiac risk factors, and self-selected
dietary adherence rates per self-report.
Results Assuming no change from baseline for participants who discontinued the
study, mean (SD) weight loss at 1 year was 2.1 (4.8) kg for Atkins (21 [53%]
of 40 participants completed, P = .009),
3.2 (6.0) kg for Zone (26 [65%] of 40 completed, P = .002),
3.0 (4.9) kg for Weight Watchers (26 [65%] of 40 completed, P < .001), and 3.3 (7.3) kg for Ornish (20 [50%] of 40
completed, P = .007). Greater effects were
observed in study completers. Each diet significantly reduced the low-density
lipoprotein/high-density lipoprotein (HDL) cholesterol ratio by approximately
10% (all P<.05), with no significant effects on
blood pressure or glucose at 1 year. Amount of weight loss was associated
with self-reported dietary adherence level (r = 0.60; P<.001) but not with diet type (r = 0.07; P = .40). For
each diet, decreasing levels of total/HDL cholesterol, C-reactive protein,
and insulin were significantly associated with weight loss (mean r = 0.36, 0.37, and 0.39, respectively) with no significant
difference between diets (P = .48, P = .57, P = .31,
Conclusions Each popular diet modestly reduced body weight and several cardiac risk
factors at 1 year. Overall dietary adherence rates were low, although increased
adherence was associated with greater weight loss and cardiac risk factor
reductions for each diet group.
Popular diets have become increasingly prevalent and controversial.1 More than 1000 diet books are now available,2 with many popular ones departing substantially from
mainstream medical advice.3 Cover stories for
major news magazines, televised debates, and cautionary statements by prominent
medical authorities4,5 have fueled
public interest and concern regarding the effectiveness and safety of such
Although some popular diets are based on long-standing medical advice
and recommend restriction of portion sizes and calories (eg, Weight Watchers),9 a broad spectrum of alternatives has evolved. Some
plans minimize carbohydrate intake without fat restriction (eg, Atkins diet),10 many modulate macronutrient balance and glycemic
load (eg, Zone diet),11 and others restrict
fat (eg, Ornish diet).12 Given the growing
obesity epidemic,13 many patients and clinicians
are interested in using popular diets as individualized eating strategies
for disease prevention.14 Unfortunately, data
regarding the relative benefits, risks, effectiveness, and sustainability
of popular diets have been limited.15- 25
We conducted a 1-year randomized trial of the dietary component of the
Atkins, Zone, Weight Watchers, and Ornish plans, aiming to determine their
realistic clinical effectiveness and sustainability for weight loss and cardiac
risk factor reduction. Of note, this study only evaluated the dietary components
and did not include other specific components that may be unique to each individual
We recruited study candidates from the Greater Boston area using newspaper
advertisements and television publicity (local news coverage). Of 1010 telephone
inquiries, 247 individuals agreed to be screened in person and 160 individuals
were enrolled at an academic medical center in Boston, Mass, from July 18,
2000, through January 24, 2002 (Figure 1).
We included adults of any age who were overweight or obese with body mass
index (calculated as weight in kilograms divided by the square of height in
meters) between 27 and 42, and having at least 1 of the following metabolic
cardiac risk factors: fasting glucose of at least 110 mg/dL (≥6.1 mmol/L),
total cholesterol of at least 200 mg/dL (≥5.2 mmol/L), low-density lipoprotein
(LDL) cholesterol of at least 130 mg/dL (≥3.4 mmol/L), high-density lipoprotein
(HDL) cholesterol of 40 mg/dL or less (≤1.0 mmol/L), triglycerides of at
least 150 mg/dL (≥1.7 mmol/L), systolic blood pressure of at least 145
mm Hg, diastolic blood pressure of at least 90 mm Hg, or current use of oral
medication to treat hypertension, diabetes mellitus, or dyslipidemia. Exclusion
criteria included unstable chronic illness, insulin therapy, urinary microalbumin
of more than 2 times normal, serum creatinine of at least 1.4 mg/dL (≥123.8 μmol/L),
clinically significant abnormalities of liver or thyroid test results, weight
loss medication, or pregnancy. Participants did not receive any monetary compensation.
All participants provided written informed consent, and the local institutional
review board approved the protocol. Our recruitment strategy was designed
to meet race and sex criteria consistent with federal guidelines.26
We administered dietary advice to small groups rather than individually.
Because not all individuals were available to meet for diet group classes
at the same time of day, we allowed participants to select 1 of 4 class times
based on personal preference. Once each of the 4 class rosters contained approximately
10 participants, 1 of the 4 diets was assigned to each group according to
a computer-generated randomized Latin-square sequence. This method was used
to ensure that each diet was administered to each of the class times only
once, therefore minimizing potential confounding between class time and diet
type. Study personnel were blinded to dietary assignments (revealed by the
study statistician) until after each class roster was finalized, to avoid
the potential for biased recruiting according to diet type. A new set of diet
classes was administered every 3 to 4 months for 4 cycles.
A single team composed of a dietitian and physician (M.L.D., J.A.G.)
administered diet-specific advice to each group, meeting for 1 hour on 4 occasions
during the first 2 months of the study. At the first meeting, the team revealed
the diet assignment and provided the corresponding rationale, written materials,
and official diet cookbook.12,27- 29 Subsequent
meetings aimed to maximize adherence by reinforcing positive dietary changes
and addressing barriers to adherence.
The Atkins diet group aimed for less than 20 g of carbohydrate daily,
with a gradual increase toward 50 g daily. The Zone group aimed for a 40-30-30
balance of percentage calories from carbohydrate, fat, and protein, respectively.
The Weight Watchers group aimed to keep total daily “points” in
a range determined by current weight. Each “point” was roughly
50 calories, and most participants aimed for 24 to 32 points daily. Lists
provided by the Weight Watchers Corporation determined point values of common
foods. The Ornish group aimed for a vegetarian diet containing 10% of calories
In an effort to isolate the effects of the dietary component of each
plan, we standardized recommendations pertaining to supplements, exercise,
and external support. We encouraged all participants to take a nonprescription
multivitamin daily, obtain at least 60 minutes of exercise weekly, and avoid
commercial support services. To approximate the realistic long-term sustainability
of each diet, we asked participants to follow their dietary assignment to
the best of their ability until their 2-month assessment, after which time
we encouraged them to follow their assigned diet according to their own self-determined
We used 2 techniques to measure dietary adherence. We asked participants
to complete 3-day food records at baseline, 1, 2, 6, and 12 months.30 Using a computerized diet analysis program (Nutritionist
Five, version 2.3, First DataBank Inc, San Bruno, Calif), we calculated the
average daily macronutrient and micronutrient intakes, and used a 10-point
score to reflect the degree to which each group achieved the specified dietary
target vs baseline intake. We also telephoned participants monthly and asked
them to rate the dietary adherence level during the previous 30 days using
a similar 10-point scale, ranging from perfect score (10) to baseline (1).
Using these scales facilitated comparisons between the 2 dietary adherence
methods. We also asked participants to report medication changes, hospitalizations,
and adverse effects during the monthly telephone calls.
We assessed outcome measures at baseline, 2, 6, and 12 months. Participants
were blinded to timing of assessments until 2 weeks before each visit, and
baseline measurements occurred within 2 weeks before dietary intervention.
Study nurses and laboratory personnel who assessed outcomes were blinded to
participants’ dietary assignment. We measured body weight using a single
calibrated scale (Detecto, Webb City, Mo) of the participants with them wearing
light clothing and no shoes. We measured waist size as the mean of 2 readings
at the umbilicus of the participant using a spring-calibrated tape measure
and blood pressure was measured as the mean of 1 reading in each arm of the
participant while he/she was sitting, using an automated instrument with digital
readout (Dinamap, Criticon Inc, Tampa, Fla). We obtained blood samples after
an overnight fast for measurement of serum total cholesterol, HDL cholesterol,
triglycerides, glucose, insulin, high-sensitivity C-reactive protein, and
creatinine levels by standard methods.31 We
used the Friedewald formula32 to calculate
LDL cholesterol. We also obtained urine samples from 24-hour collections for
measurement of total protein, nitrogen, and creatinine levels. We documented
changes in exercise category (vigorous, moderate, mild, or minimal) according
The primary end point was mean absolute change from baseline weight
at 1 year. Using t tests and a 2-sided type I error
of 5%, we estimated that 40 participants in each group would be necessary
to achieve 80% power to detect a weight change of 2% from baseline or 3% between
Analysis of variance was used to assess differences in baseline variables
between diet groups, and independent t tests were
used to compare baseline variables between study participants who discontinued
the study with those participants who remained. Absolute changes for each
outcome variable at 2, 6, and 12 months were normally distributed for weight
loss and cardiac risk variables but not for dietary variables. To assess the
null hypothesis of no change from baseline, we used 1-sample t test for normally distributed variables and Wilcoxon rank sum test
for skewed variables. Missing data were replaced with baseline data for a
primary intent-to-treat analysis or excluded for a secondary completers analysis.
To compare the adherence data obtained from diet records and self-reports,
we used Pearson correlation coefficient in a single analysis that paired the
2 mean scores for each diet across 5 time points. We used linear regression
to assess the relationship between changes in weight, dietary adherence variables,
and cardiac risk factors, and to assess the independent effects of potentially
confounding variables, including baseline characteristics, and changes in
exercise and medication use. We used SPSS version 10.1 (SPSS Inc, Chicago,
Ill) for all statisticall analyses. All P values
were 2-sided; P≤.05 was considered statistically
The 40 participants in each of the 4 diet groups were well matched in
terms of baseline characteristics (Table 1).
Age, race, sex, body mass index, and metabolic characteristics generally matched
those of the overweight population in the United States.13 Baseline
characteristics did not differ significantly between diet groups and regression
models adjusting for these (eg, hyperglycemia, baseline insulin levels) or
other potentially confounding variables such as time of diet class demonstrated
no confounding effects.
Of the 160 participants, the mean (SD) age was 49 (11) years (range,
22-72 years) and 81 were women (n=21 in Atkins, n=20 in Zone, n=23 in Weight
Watchers, n=17 in Ornish groups; P = .90
for sex difference between diets). Compared with men, women had significantly
lower mean baseline weight (93 vs 106 kg), waist size (103 vs 114 cm), diastolic
blood pressure (74 vs 78 mm Hg), and triglyceride levels (150 vs 188 mg/dL
[1.7 vs 2.1 mmol/L]) (all P<.05), and higher mean
levels of C-reactive protein (4.8 vs 3.3 mg/L) and HDL cholesterol (52 vs
41 mg/dL [1.35 vs 1.06 mmol/L]). Women were also more likely to be nonwhite
(38% vs 11%).
The number of participants who did not complete the study at months
2, 6, and 12 were 34 (21%), 61 (38%), and 67 (42%), respectively. At 1 year,
there was a nonsignificant trend (P = .08)
toward a difference in discontinuation rates between the more extreme diets
(48% for Atkins and 50% for Ornish) and moderate diets (35% for Zone and 35%
for Weight Watchers). Twenty-seven of 61 participants who discontinued before
6 months were evaluated at 2 months (mean weight loss, 2.6 kg) and 10 of 67
participants who discontinued before 12 months were evaluated at 6 months
(mean weight loss, 1.3 kg). Individuals who discontinued the study had less
formal education (P = .001) and lower baseline
diastolic blood pressure (74 vs 78 mm Hg, P = .02)
than those who completed. The most common reasons cited for discontinuation
of the study were that the assigned diet was too hard to follow or not yielding
enough weight loss. We were unable to identify any diet-related adverse event
or serious adverse effects during the study. We found no evidence of clinically
significant renal impairment in any of the diet groups.
Dietary intake according to an intent-to-treat analysis of 3-day diet
records is shown in Table 2. At baseline,
147 (92%) of the participants submitted food records. Mean total energy intake
was 2059 calories daily, with 46.4%, 34.5%, and 17.6% of calories derived,
respectively, from carbohydrate, fat, and protein. There were no significant
caloric or macronutrient differences between diet groups at baseline. For
each group, dietary adherence as assessed by diet records decreased progressively
with time, although the specifically targeted dietary parameters for each
diet were significantly different from baseline (all P < .01)
at each time point, according to both the primary and secondary analyses.
At 1 year, the mean caloric reductions from baseline were 138 for Atkins,
251 for Zone, 244 for Weight Watchers, and 192 for Ornish groups (all P<.05, P = .70 between
Group mean adherence scores according to diet records and self-assessment
were highly associated for the duration of the study (Pearson r = 0.90; P<.001). As with diet
records, adherence according to self-report gradually decreased over time,
and to a similar extent in each diet group (Figure
2). Nevertheless, approximately 25% of participants in each diet
group sustained a mean adherence level of at least 6 of 10, which appeared
to delineate a clinically meaningful adherence level.
According to the primary intent-to-treat analysis (Table 3) and the secondary analysis that excluded missing data (Table 4), all 4 diets resulted in modest statistically
significant weight loss at 1 year, with no statistically significant differences
between diets (P = .40). In each diet group,
approximately 25% of the initial participants sustained a 1-year weight loss
of more than 5% of initial body weight and approximately 10% of participants
lost more than 10% of body weight. Weight reductions were highly associated
with waist size reductions for all diets (Pearson r = 0.86
at 1 year; P<.001), with no significant difference
between diets. In women, mean (SD) body weight decreased by 2.4 (5.1) kg (2.5%
change from baseline) and waist size by 2.3 (4.5) cm, whereas in men body
weight decreased by 3.3 (6.4) kg (3.1% change from baseline) and waist size
by 3.1 (5.8) cm at 1 year (P = .30 for
In contrast with the absent association between diet type and weight
loss (r = 0.07; P = .40),
we observed a strong curvilinear association between self-reported dietary
adherence and weight loss (r = 0.60; P<.001) that was almost identical for each diet (Figure 3). Participants in the top tertile of
adherence lost 7% of body weight on average.
According to the primary intent-to-treat analysis (Table 3), all diets achieved modest, although statistically significant,
improvements in several cardiac risk factors at 1 year. All diets reduced
mean LDL cholesterol levels at 1 year, although this did not reach statistical
significance in the case of the Atkins group (P = .07).
All diets significantly increased mean HDL cholesterol levels, except in the
Ornish diet group (P = .60). The LDL/HDL
ratio decreased approximately 10% in each diet group (all P<.05). No diet program significantly altered triglycerides, blood
pressure, or fasting glucose at 1 year. The lower carbohydrate diets (Atkins
and Zone) were more likely to reduce triglycerides, diastolic blood pressure,
and insulin in the short term, although the Atkins diet failed to significantly
reduce mean fasting insulin levels at 1 year (P = .26).
All the diets reduced 1-year C-reactive protein levels by approximately 15%
to 20%, although the reduction did not reach statistical significance in the
case of the Zone diet (P = .09). The secondary
analysis, which excluded missing data (Table 4), demonstrated larger but otherwise similar changes overall.
The amount of weight loss predicted the amount of improvement in several
cardiac risk factors (Figure 4). For
each diet, weight loss was significantly associated with changes in total/HDL
cholesterol ratio (r = –0.36), C-reactive
protein (r = –0.37), and insulin
levels (r = –0.39), regardless of
diet type (P = .48, P = .57, P = .31, respectively,
for difference between diets). No diet significantly worsened any cardiac
risk factor in association with weight loss or dietary adherence at 1 year.
Exercise levels, according to participant report (vigorous, moderate,
mild, minimal), were modestly increased from baseline throughout the trial
(all P<.05), and to a similar extent for each
diet group (P = .70 between diets). At
1 year, the numbers of participants with increased and decreased exercise
levels from baseline were 11 and 2 for Atkins, 10 and 7 for Zone, 14 and 3
for Weight Watchers, and 8 and 3 for Ornish groups, respectively. The amount
of weight loss was associated with changes in exercise level (r = 0.27; P=.001), with no significant
differences between diets (P = .70). After
accounting for dietary adherence, there was no significant association between
change in exercise and change in body weight or any cardiac risk factor at
The number of prescription medications (mean, 2.4) did not significantly
change in the 126 participants who remained in the study for at least 2 months.
The net change in total number of prescription medications for the Atkins,
Zone, Weight Watchers, and Ornish groups was +7, –4, –7, and +5,
respectively (P = .16 for difference between
diets). Adjusting for changes in baseline medication use did not materially
affect the study outcomes. For example, 4 to 7 participants in each group
were initially taking cholesterol-lowering medication, which was discontinued
by 1 individual in the Zone group and initiated during the study by primary
care physicians for 1 each in the Atkins and Weight Watchers groups and for
3 in the Zone group. When individuals who initiated cholesterol-lowering medication
were excluded from the intent-to-treat analysis, the reductions in LDL/HDL
cholesterol ratios observed with each diet remained statistically significant,
and associations between weight loss and lipid changes were unchanged or slightly
In our randomized trial, we found that a variety of popular diets can
reduce weight and several cardiac risk factors under realistic clinical conditions,
but only for the minority of individuals who can sustain a high dietary adherence
level. Despite a substantial percentage of participants who could sustain
meaningful adherence levels, no single diet produced satisfactory adherence
rates and the progressively decreasing mean adherence scores were practically
identical among the 4 diets. The higher discontinuation rates for the Atkins
and Ornish diet groups suggest many individuals found these diets to be too
extreme. To optimally manage a national epidemic of excess body weight33 and associated cardiac risk factors, practical techniques
to increase dietary adherence rates are urgently needed.
One way to improve dietary adherence rates in clinical practice may
be to use a broad spectrum of diet options, to better match individual patient
food preferences, lifestyles, and cardiovascular risk profiles. Participants
in our study were not allowed to choose their dietary assignment; however,
we suspect adherence rates and clinical improvements would have been better
if participants had been able to freely select from the 4 diet options. Our
findings challenge the concept that 1 type of diet is best for everybody and
that alternative diets can be disregarded. Likewise, our findings do not support
the notion that very low carbohydrate diets are better than standard diets,
despite recent evidence to the contrary.17,22,23,25
Our results support a growing body of research suggesting that carbohydrate
restriction and saturated fat restriction have different effects on cardiovascular
risk profiles. Low carbohydrate diets consistently increase HDL cholesterol,17,20 and low–saturated fat diets
consistently decrease LDL cholesterol levels.34 Low
carbohydrate diets have typically been more effective for short-term reduction
of serum triglycerides, glucose, and/or insulin.17,19,22,23,35,36 These
findings may suggest to some clinicians that the degree to which a patient
exhibits features of the metabolic syndrome might guide the degree of carbohydrate
restriction to recommend. In the long run, however, sustained adherence to
a diet rather than diet type was the key predictor of weight loss and cardiac
risk factor reduction in our study.
The clinical significance of diet-induced changes in HDL cholesterol
is unclear. High-carbohydrate/low-fat diets typically reduce or fail to increase
HDL cholesterol levels, but insufficient data exist to determine whether this
is harmful or benign in terms of cardiac events or atherosclerosis progression.34,37,38 Similarly, the increase
in HDL cholesterol associated with low-carbohydrate/high-fat diets is of unclear
benefit due to a lack of relevant dietary intervention trials. Increased saturated
fat intake may potentially contribute to HDL cholesterol increases in the
case of the Atkins diet, although we observed no such association between
changes in HDL cholesterol and saturated fat in our study. The reduction in
LDL/HDL cholesterol ratio observed for each diet is suggestive but not conclusive
of net beneficial effects on lipid profiles. Clearly, the cardiovascular and
other health effects of dietary alternatives require additional study.
By design, our study provided a limited amount of support beyond the
initial 2 months to estimate the real-world effectiveness and sustainability
of the diets when a long-term support system was lacking. A benefit of this
approach was the enhanced ability to demonstrate a dose-response relationship
between dietary adherence levels, weight loss, and clinical benefits. A drawback
is that this approach is poorly suited to determine the effects of each diet
in highly adherent individuals. Research studies and clinical programs that
aim to maximize adherence to dietary and other lifestyle recommendations are
known to obtain greater clinical benefits.39,40
Our study has several limitations. Our study was designed to identify
the clinical strengths and weaknesses of each diet under identical conditions
but was not necessarily designed to identify a “best diet.” If
one diet produces more weight loss or cardiac risk reduction than the other
diets do, a much larger sample size would probably be required to detect such
differences under similar conditions. Our study had a relatively high rate
of attrition, which confounds the interpretation of the results because the
magnitude of the results depends on the accuracy of an unverifiable assumption.
The assumption that participants who discontinued the study were unchanged
from baseline is reasonable but imprecise.41 Nevertheless,
we believe our general findings are reasonably valid based on 3 observations:
participants who discontinued were reasonably similar to the other participants
from a demographic and clinical perspective, the participants who discontinued
had evidence of weight loss rather than weight gain before discontinuing,
and we obtained meaningful (albeit modest) results despite a rather conservative
approach to handling the missing data. Our study was limited in its ability
to exclude long-term safety risks or occasional dangerous adverse effects
resulting from the diets, even though we found no short-term safety risks
in our study. Finally, the measurements of dietary intake and adherence relied
on self-reporting and are therefore subjective.
In conclusion, poor sustainability and adherence rates resulted in modest
weight loss and cardiac risk factor reductions for each diet group as a whole.
Cardiac risk factor reductions were associated with weight loss regardless
of diet type, underscoring the concept that adherence level rather than diet
type was the key determinant of clinical benefits. Cardiovascular outcomes
studies would be appropriate to further investigate the potential health effects
of these diets. More research is also needed to identify practical techniques
to increase dietary adherence, including techniques to match individuals with
the diets best suited to their food preferences, lifestyle, and medical conditions.
Corresponding Author: Michael L. Dansinger,
MD, Atherosclerosis Research Laboratory, Tufts-New England Medical Center,
Box 216, Boston Dispensary 342, 750 Washington St, Boston, MA 02111 (firstname.lastname@example.org).
Author Contributions: Dr Dansinger had full
access to all of the data in the study and takes responsibility for the integrity
of the data and the accuracy of the data analysis.
Study concept and design: Dansinger, Griffith,
Acquisition of data: Dansinger, Gleason, Schaefer.
Analysis and interpretation of data: Dansinger,
Gleason, Selker, Schaefer.
Drafting of the manuscript: Dansinger, Griffith,
Critical revision of the manuscript for important
intellectual content: Dansinger, Gleason, Griffith, Selker, Schaefer.
Statistical analysis: Dansinger, Griffith.
Obtained funding: Dansinger, Selker, Schaefer.
Administrative, technical, or material support:
Dansinger, Gleason, Selker, Schaefer.
Study supervision: Selker, Schaefer.
Funding/Support: This study was supported by
grants MO1-RR00054 from the General Clinical Research Center via the National
Center for Research Resources of the National Institutes of Health (NIH);
HL57477 from the NIH; contract 53-1950-5-003 from the US Department of Agriculture;
and P30DK46200 from the Human Metabolic and Genetics Core Laboratory of the
Boston Obesity Nutrition Research Center program. Dr Dansinger was supported
by grant T32 HS00060 from the Agency for Healthcare Research and Quality.
Role of the Sponsors: The General Clinical
Research Center scientific staff provided consultation in the design of the
study. The General Clinical Research Center nursing staff provided assistance
with the data collection. No sponsor participated in the analysis or interpretation
of the data, manuscript preparation, review, or approval, or the decision
Acknowledgment: We thank Wenjun Li, PhD, from
the University of Massachusetts Medical School, Division of Preventive and
Behavioral Medicine, for statistical assistance; Judith McNamara, MT, and
Kourosh Zonous-Hashemi, BS, from the Lipid Metabolism Laboratory, Jean Mayer
USDA Human Nutrition Research Center, Tufts University, for performing the
lipoprotein analyses; Elias Seyoum, PhD, from the Nutrition Evaluation Laboratory,
Jean Mayer USDA Human Nutrition Research Center, Tufts University, for performing
the insulin assays; the General Clinical Research Center staff from Tufts-New
England Medical Center for technical assistance; Kendrin Sonneville, MS, RD,
and Jacquelyn Stamm, MS, RD, for performing diet record analyses; and Sylvia
Peterson, for administrative support.