ArticlePDF Available

Dietary adherence and weight loss success among overweight women: Results from the A TO Z weight loss study

Authors:

Abstract and Figures

Dietary adherence has been implicated as an important factor in the success of dieting strategies; however, studies assessing and investigating its association with weight loss success are scarce. We aimed to document the level of dietary adherence using measured diet data and to examine its association with weight loss success. Secondary analysis was performed using data from 181 free-living overweight/obese women (mean+/-s.d. age=43+/-5 years, body mass index=31+/-4 kg m(-2)) participating in a 1-year randomized clinical trial (the A TO Z study) comparing popular weight loss diets (Atkins, Zone and Ornish). Participants' dietary adherence was assessed as the difference between their respective assigned diet's recommended macronutrient goals and their self-reported intake. Association between dietary adherence and 12-month weight change was computed using Spearman's correlations. Differences in baseline characteristics and macronutrient intake between the most and least adherent tertiles for diet groups were compared using t-tests. Within each diet group, adherence score was significantly correlated with 12-month weight change (Atkins, r(s)=0.42, P=0.0003; Zone, r(s)=0.34, P=0.009 and Ornish, r(s)=0.38, P=0.004). Twelve-month weight change in the most vs least adherent tertiles, respectively, was -8.3+/-5.6 vs -1.9+/-5.8 kg, P=0.0006 (Atkins); -3.7+/-6.3 vs -0.4+/-6.8 kg, P=0.12 (Zone) and -6.5+/-6.8 vs -1.7+/-7.9 kg, P=0.06 (Ornish). Regardless of assigned diet groups, 12-month weight change was greater in the most adherent compared to the least adherent tertiles. These results suggest that strategies to increase adherence may deserve more emphasis than the specific macronutrient composition of the weight loss diet itself in supporting successful weight loss.
Content may be subject to copyright.
ORIGINAL ARTICLE
Dietary adherence and weight loss success among
overweight women: results from the A TO Z weight
loss study
S Alhassan
1,2
, S Kim
2
, A Bersamin
2
, AC King
2
and CD Gardner
2
1
Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA and
2
Stanford Prevention Research
Center, Stanford University School of Medicine, Stanford, CA, USA
Background: Dietary adherence has been implicated as an important factor in the success of dieting strategies; however, studies
assessing and investigating its association with weight loss success are scarce.
Objective: We aimed to document the level of dietary adherence using measured diet data and to examine its association with
weight loss success.
Design: Secondary analysis was performed using data from 181 free-living overweight/obese women (mean±s.d. age ¼43±5
years, body mass index ¼31±4kgm
2
) participating in a 1-year randomized clinical trial (the A TO Z study) comparing popular
weight loss diets (Atkins, Zone and Ornish). Participants’ dietary adherence was assessed as the difference between their
respective assigned diet’s recommended macronutrient goals and their self-reported intake. Association between dietary
adherence and 12-month weight change was computed using Spearman’s correlations. Differences in baseline characteristics
and macronutrient intake between the most and least adherent tertiles for diet groups were compared using t-tests.
Results: Within each diet group, adherence score was significantly correlated with 12-month weight change (Atkins, r
s
¼0.42,
P¼0.0003; Zone, r
s
¼0.34, P¼0.009 and Ornish, r
s
¼0.38, P¼0.004). Twelve-month weight change in the most vs least
adherent tertiles, respectively, was 8.3±5.6 vs 1.9±5.8 kg, P¼0.0006 (Atkins); 3.7±6.3 vs 0.4±6.8 kg, P¼0.12 (Zone)
and 6.5±6.8 vs 1.7±7.9 kg, P¼0.06 (Ornish).
Conclusions: Regardless of assigned diet groups, 12-month weight change was greater in the most adherent compared to the
least adherent tertiles. These results suggest that strategies to increase adherence may deserve more emphasis than the specific
macronutrient composition of the weight loss diet itself in supporting successful weight loss.
International Journal of Obesity (2008) 32, 985–991; doi:10.1038/ijo.2008.8; published online 12 February 2008
Keywords: dietary adherence; weight loss; overweight/obese premenopausal women; popular diets
Introduction
One in three US adults report currently trying to lose
weight;
1
among overweight and obese individuals the
proportion is even higher. Despite the ubiquity of weight
loss efforts, obesity rate is far from decreasing; rather, the
rate is ever increasing and currently 65% of US adults are
overweight or obese,
2
attesting to the ineffectiveness of most
weight loss efforts. Indeed, more than half of dieters regain
the majority of their weight loss within the first 12 months
and less than one-third are able to avoid weight regain over a
3-year period.
3,4
Given the well-recognized benefits of
weight loss among overweight and obese individuals,
5–8
these findings are discouraging and threaten efforts to curb
the rise in national obesity rates.
The common failure in following traditional weight loss
strategies (for example, increasing physical activity and
decreasing caloric intake) has prompted a surge in alter-
native diet approaches. However, these alternative dieting
approaches, including extreme carbohydrate restriction
(Atkins), extreme fat restriction (Ornish) or replacing
carbohydrates with protein (Zone) have led to only modest
weight loss.
9–13
Poor dietary adherence has been implicated
in the lack of success of popular and traditional dieting
strategies. For example, in a recent review on low-calorie
diets, the authors stated that the lack of success of such diets
was likely due to difficulties with participants adherence.
14
Received 4 September 2007; revised 18 December 2007; accepted 10 January
2008; published online 12 February 2008
Correspondence: Dr S Alhassan, Department of Kinesiology, University of
Massachusetts Amherst, 150 Totman Building, 30 Eastman Lane, Amherst, MA
01003-9258, USA.
E-mail: alhassan@kin.umass.edu
International Journal of Obesity (2008) 32, 985 –991
&
2008 Nature Publishing Group All rights reserved 0307-0565/08
$
30.00
www.nature.com/ijo
Overall, studies investigating dietary adherence level and its
association with weight loss success in randomized clinical
trials in a large sample are scarce. Even the few studies that
have examined the associations between dietary adherence
and weight loss were constrained by a number of limitations
such as self-reported measure of adherence measure, small
sample sizes, low retention rate and short study follow-up
period.
10,15–17
Therefore, to address some of the potential
limitations of previous work, we performed the present
analyses to determine the level of adherence from a 1-year
randomized clinical trial comparing the effectiveness of four
popular diets in overweight/obese women using carefully
measured diet data and to examine the association between
the dietary adherence and magnitude of weight loss.
Methods
Participants
Data for these analyses came from a study originally
designed to compare the relative effectiveness of one
traditional and three popular weight loss diets in a sample
of 311 overweight and obese women. A detailed description
of the primary study protocol and results has been reported
elsewhere.
9
Participants, recruited primarily through news-
paper advertisements, were invited to enroll if they were
25–50 years of age, had a body mass index (BMI) of
27–40 kg m
2
, stable weight over the previous 2 months
and were stable for X3 months on their medications.
Women were excluded if they had cardiovascular, metabolic
or pulmonary disease; were hypertensive (except those stable
on antihypertensive medications); were taking medications
known to affect weight/energy expenditure or lipid metabo-
lism; reported an alcohol intake of X3 drinks per day; or
were lactating, pregnant or planning to become pregnant
within the next year. All participants provided written
informed consent. The study was approved by the Stanford
University Human Subjects Committee.
Following baseline data collection, participants were
randomly assigned to follow one of four diet books:
Dr. Atkins’ New Diet Revolution,
18
Enter the Zone,A Dietary
Roadmap,
19
Eat More Weigh Less
20
or The LEARN Program for
Weight Management.
21
Each participant was scheduled to
attend eight 1-h, weekly evening classes over 2 months. A
registered dietitian led the classes and reviewed approxi-
mately one-eighth of the assigned books at each class.
Participants were instructed to master their assigned diet by
the end of the 2-month class, and then to continue following
their diets on their own for the subsequent 10 months. Class
sizes ranged from 15 to 22 and participants were enrolled in
four cohorts, the first of which began in the spring of 2003
and the last of which finished in the fall of 2005.
Unlike the Atkins, Zone or Ornish diets that are based on
clearly defined macronutrient manipulations, the LEARN
diet is based on total behavior modification and general
dietary guidelines. Due to the multiple dimensions of the
LEARN program’s recommended goals, a measure of dietary
adherence comparable with the other diets could not be
created for the LEARN diet; therefore, the 79 participants
assigned to the LEARN diet group were excluded from the
current analyses.
Dietary assessment
Dietary information was obtained at baseline and each of
three post-randomization time points (2, 6 and 12 months).
Dietary intake data were collected by telephone-administered,
3-day, unannounced, 24-h dietary recalls using Nutrition Data
System for Research software (Nutrition Coordinating Center
(NCC), University of Minnesota, versions 4.05.33 (2002),
4.06.34 (2003) and 5.0.35 (2004)). Data collectors were trained
and certified by the NCC in Minneapolis. The recalls occurred
on two weekdays and one weekend day per time point, on
nonconsecutive days whenever possible. Local foods not
found in the comprehensive database were added to the
database manually. A ‘Food Amounts Booklet’ was used to
assist participants with portion size estimation. The dietary
intake data were 96.8% complete.
Measure of adherence
Adherence was assessed based on the agreement between
the primary macronutrient goal(s) of the assigned diet and
a participant’s reported dietary intake. An average of all
available dietary recalls at each time point was used to
calculate adherence scores. For participants assigned to the
Atkins diet, adherence was calculated as the difference
between the reported and recommended daily carbohydrate
intake, which was p20 g carbohydrate per day at 2 months
for the induction phase and p50 g carbohydrate per day for
the ongoing weight loss phase of the subsequent 10 months.
For example, an estimated intake of 40 g carbohydrate per
day at 2 months for participant assigned to the Atkins diet
would yield an adherence score of 20 (calculated by
subtracting 20 from 40). An estimated intake of 85 g at 6 or
12 months would yield an adherence score of 35 (calculated
by subtracting 50 from 85).
For participants assigned to the Zone diet, dietary
adherence was calculated as the difference between the
reported and recommended distribution of energy intake
from carbohydrate:fat:protein, which was 40:30:30. Specifi-
cally, this was calculated using a Mahalanobis distance
equation, which can be used to measure the similarity
between a set of actual conditions relative to a set of ideal
conditions.
22
The equation used to calculate distance from
the recommended goal at each of the three post-randomiza-
tion time points was
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
½ðXCHO 40Þ2þðXFAT 30Þ2þðXPRO 30Þ2=3
q
where X
CHO
,X
FAT
and X
PRO
were a participant’s observed
percent of energy from carbohydrate, fat and protein,
Dietary adherence and weight loss success
S Alhassan et al
986
International Journal of Obesity
respectively. For example, dietary adherence score for a
participant assigned to the Zone diet with a macronutrient
distribution of 45% carbohydrate, 29% fat and 26% protein
at any of the three post-randomization time points would be
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
½ð45 40Þ2þð29 30Þ2þð26 30Þ2=3¼3:74
q
For participants assigned to the Ornish group, dietary
adherence was calculated as the difference between the
observed and recommended daily total fat intake (p10% of
energy from fat) at all three post-randomization time points.
For example, an estimated intake of 21% of energy from fat
for a participant assigned to the Ornish group would yield an
adherence score of 11 (calculated by subtracting 10 from 21).
For all diets, a score of zero was awarded if a participant
met or exceeded their assigned diet’s macronutrient
distribution goals. A total dietary adherence score for each
participant was then calculated as the average of the three
post-randomization time points (2, 6 and 12 month). The
adherence scores measured a degree of deviation from the
recommended dietary goals; a lower score reflects better
adherence and a higher score reflects greater nonadherence.
Anthropometric measurements
Body weight was measured in light clothing to the nearest
0.1 kg using a calibrated clinical scale. Standing height was
measured to the nearest millimeter using a standard wall-
mounted stadiometer. BMI was calculated as the weight in
kilograms divided by the square of the height in meters.
Percent body fat was determined by dual-energy X-ray
absorptiometry using pencil-beam mode on the Hologic
QDR-2000 (first three cohorts) and the array mode on a
Hologic QDR 4500 densitometer (last cohort) (Hologic Inc.,
Waltham, MA, USA).
Statistical analysis
Descriptive data are expressed as means±standard devia-
tions (s.d.). Association between dietary adherence score and
12-month weight change was computed using Spearman’s
nonparametric correlations, making no assumptions about
the distributions. Tertiles of adherence score were deter-
mined for each diet group. Statistical testing of differences
between the most (Tertile 1) and least (Tertile 3) adherent
tertile for each diet group was conducted using t-tests. All
analyses were performed separately within each diet group.
The metrics used to define dietary adherence scores were
dramatically different for the three diet groups; therefore
adherence scores were not directly comparable between
groups. To create comparable adherence scores, thereby
allowing us to assess between-group differences, participants’
average adherence scores were converted into z-scores.
Between-group differences were assessed using a general
linear model. All statistical analyses were performed using
SAS version 9.1 (SAS Institutes Inc., Cary, NC, USA).
Results
Of the 232 women originally randomized to the Atkins, Zone
and Ornish diets (Atkins, n¼77; Zone, n¼79 and Ornish,
n¼76), dietary data were available at all four time points
for 181 women (78%) (Atkins, n¼68; Zone, n¼57 and
Ornish, n¼56). Baseline characteristics are presented in
Table 1. Total energy intake was not different among diet
groups at any post-randomization time point (Table 2).
However, relative to baseline there was a significant decrease
in reported energy intake at all post-randomization time
points for all groups combined (Po0.0001). As expected, at
Table 1 Baseline characteristics
Atkins (n¼68) Zone (n¼57) Ornish (n¼56)
Age (years) 43±542
±642
±6
Education (years) 16±216
±216
±2
Weight (kg) 83±12 82±12 85±10
Height (cm) 163±6 164±7 165±7
BMI (kg m
2
)31
±431
±331
±4
Body fat (%) 39±538
±639
±6
Abbreviation: BMI, body mass index.
Table 2 Macronutrient intake for diet groups
Atkins (n¼68) Zone (n¼57) Ornish (n¼56)
Energy (kcal day
1
)
Baseline 1908±507 2031±581 1860±491
2 months 1377±346 1458±497 1402±400
6 months 1525±380 1506±346 1507±507
12 months 1599±494 1594±523 1505±437
Carbohydrates (g)
Baseline 218±81 234±88 222±66
2 months 55±33 152±63 219±76
6 months 110±67 165±53 201±88
12 months 135±71 180±73 198±75
Carbohydrates (% energy)
Baseline 45±11 456 ±948
±7
2 months 16±941
±863
±11
6 months 28±14 44±953
±14
12 months 34±14 45±11 52±12
Protein (% energy)
Baseline 17±416
±316
±3
2 months 28±524
±617
±4
6 months 23±620
±518
±5
12 months 21±520
±518
±4
Fat (% energy)
Baseline 36±836
±735
±7
2 months 56±735
±721
±8
6 months 48±12 36±828
±11
12 months 44±12 35±830
±10
Dietary fiber (g)
Baseline 17±618
±917
±7
2 months 11±617
±722
±10
6 months 14±616
±819
±12
12 months 15±717
±919
±9
Dietary adherence and weight loss success
S Alhassan et al
987
International Journal of Obesity
post-randomization time points the diets were statistically
different in macronutrient intake. Carbohydrate intake was
lowest for the Atkins group, intermediate for the Zone group
and highest for the Ornish group. The fat and protein intake
trends were in the opposite direction.
Adherence scores for each diet group are presented in
Table 3. Overall adherence scores for the Atkins group,
averaged over the three post-randomization time points (2, 6
and 12 months), ranged from 2.4 to 204.1. For the Zone
group, adherence scores determined using the Mahalanobis
distance score ranged between 6.0 and 25.9. For the Ornish
group adherence scores ranged from 0 to 40.9. In all three
groups, the level of adherence diminished progressively from
2 to 6 to 12 months (that is, adherence score numbers
increased).
Twelve-month weight change (kg) was 5.3, 2.3 and
3.0 for the Atkins, Zone and Ornish groups, respectively.
Average weight change from baseline for each diet group
at each post-randomization time point is presented in
Table 3. Within each diet group, overall adherence score
(that is, average of the three post-randomization scores) was
significantly correlated with 12-month weight change
(Atkins, r
s
¼0.42, P¼0.0003; Zone, r
s
¼0.34, P¼0.009 and
Ornish, r
s
¼0.38, P¼0.004).
Across all three diet groups, only one participant, in the
Ornish group, met the criteria for absolute adherence at
all three post-randomization time points. A total of nine
participants from the three diet groups met the absolute
adherence criteria for at least two of the three post-
randomization time points (Atkins, n¼6; Ornish, n¼1 and
Zone, n¼2). Given these low numbers, no further data are
presented comparing absolutely adherent vs nonadherent
participants. Further analyses were based on relative adher-
ence (tertiles).
Baseline demographic and anthropometric measures, for
the most (Tertile 1) and least adherent (Tertile 3) individuals
within each diet group are presented in Table 4. With the
exception of education level for the Ornish group, baseline
measures were similar for all three diet groups. Selected
dietary macronutrient intake values, averaged across the
three post-randomization time points, are presented for
Tertiles 1 and 3 for all three diet groups in Table 5. All
reported macronutrient intakes were significantly different
between Tertile 1 and 3 for the Atkins group. For Zone, the
Table 3 Adherence scores and weight loss by time point and diet group
(mean±s.d.)
Atkins (n¼68) Zone (n¼57) Ornish (n¼56)
Adherence score
2 months 35.2±32.7 11.4±5.6 11.4±7.8
6 months 62.6±64.7 13.7±6.5 18.3±11.0
12 months 85.8±70.5 15.0±6.9 19.8±10.4
Average 61.2±48.7 13.3±4.5 16.5±7.9
Weight loss (kg)
2 months 4.9±2.6 2.9±3.0 3.0±2.2
6 months 6.7±5.9 2.9±5.9 3.1±4.8
12 months 5.3±7.2 2.2±6.3 3.0±6.8
Table 5 Average macronutrient intakes for most (Tertile 1) and least (Tertile 3) adherent participants
Atkins Zone Ornish
Most adherent Least adherent Most adherent Least adherent Most adherent Least adherent
Energy (kcal day
1
) 1345±296 1684±327
w
1433±266 1534±353 1324±410 1543±330
Carbohydrate (g/CHO) 52±10 155±43
z
150±33 172±64 220±81 181±54
Carbohydrate (% energy) 17±436
±7
z
42±345
±12 65±647
±9
z
Protein (% energy) 27±320
±4
z
25±320
±5
z
18±418
±3
Fat (% energy) 55±642
±7
z
33±336
±718
±534
±6
z
Dietary fiber (g) 10±316
±5
z
15±518
±924
±815
±5
w
w
Significant difference at Po0.01.
z
Significant difference at Po0.0001.
Table 4 Baseline characteristics for most (Tertile 1) and least (Tertile 3) adherent participants (mean±s.d.)
Atkins Zone Ornish
Most adherent Least adherent Most adherent Least adherent Most adherent Least adherent
Adherence score (range) 15.5±8.5 (2.4–31.3) 115.1±42.7 (71.0–204.1) 8.9±1.6 (6.0–10.9) 18.3±3.5 (14.8–25.9) 8.1±4.5 (0–12.6) 24.3±5.8 (19.1–40.9)
Age (years) 43±442
±740
±640
±744
±542
±6
Education (years) 16±216
±216
±216
±217
±115
±2*
Weight (kg) 86.1±13.9 83.5±11.0 83.2±14.0 85.6±10.9 87.8±8.6 88.1±11.4
BMI (kg m
2
)32.1
±3.4 31.5±3.6 31.6±3.6 31.0±3.4 32.1±2.6 32.5±4.3
Body fat (%) 42.0±6.7 39.5±6.1 40.6±5.0 39.5±6.4 42.7±6.1 40.2±5.6
Abbreviation: BMI, body mass index. *Significant difference at Po0.05 for least vs most adherent tertiles within each diet group.
Dietary adherence and weight loss success
S Alhassan et al
988
International Journal of Obesity
only macronutrient difference that achieved statistical
significance was protein intake, which was higher in Tertile
1. Compared to Tertile 3, Tertile 1 for the Ornish group
consumed a diet that was significantly higher in total
carbohydrate and dietary fiber but lower in fat. Atkins was
the only group with a significant difference in energy intake
between Tertile 1 and 3 (estimated energy intake was not
significantly different between Tertile 1 and 3 for the other
two diet groups). The difference in average caloric deficit
(baseline caloric intakeaverage caloric intake for the three
post-randomization time points) between Tertile 1 and 3
within each diet group (Atkins, 21±34, P¼0.85; Zone,
70±2, P¼0.69 and Ornish, 53±269, P¼0.71) was not
statistically significant. In the most adherent tertile
(Tertile 1), average caloric deficit was significantly correlated
to 12-month weight change for the Atkins group (r
s
¼0.45,
P¼0.04) but not for the Zone (r
s
¼0.22, P¼0.37) or the
Ornish group (r
s
¼0.34, P¼0.17).
Participants in the most adherent tertile for the Atkins,
Zone and Ornish groups lost approximately 10, 5 and 7%,
respectively, of their baseline body weight. The magnitude
of the difference in average weight loss between the least
and most adherent tertiles for the Atkins, Zone and
Ornish groups was 6.3 kg (P¼0.0006), 3.4 kg (P¼0.12)
and 4.7 kg (P¼0.06), respectively (Figure 1). Average
adherence score and 12-month weight change were not
significantly different between the three diet groups for
individuals with average adherence score above or below
their respective group mean (P40.05).
Discussion
The objective of this secondary analysis was to explore the
role of dietary adherence on weight loss for three popular
diets from a recent weight loss study.
9
Adherence was
significantly correlated with 12-month weight change with-
in each of the three diet groups. Mean difference in 12-
month weight change between the most and least adherent
tertiles was only significant in the Atkins group. The average
12-month weight change, in absolute numbers, was slightly
higher for the Atkins group (8.3±5.6 kg) than for Zone
(3.7±6.3 kg) or Ornish groups (6.5±6.8 kg) in the most
adherent tertile.
Although dietary adherence is an important factor in any
dietary weight loss program, few studies have systematically
measured dietary adherence and examined its association
with weight loss success. Westman et al.
16
reported a
significant correlation between dietary adherence (assessed
through self-report and urinary ketones) and weight loss
for 41 participants following a very low carbohydrate diet
(o25 g per day) for 6 months. However, the study was
limited by a small sample size. Dansinger et al.
10
conducted a
weight loss study comparing the Atkins, Zone, Weight
Watchers and Ornish diets and collected self-reported
adherence data using Likert scales. These investigators
concluded that adherence was a stronger predictor of weight
loss success than diet group assignment, but the 12-month
dropout rates of 35–50% among their four diet groups
present a limitation. Heshka et al.
17
reported a significant
association between adherence to the Weight Watcher
program and weight loss success but adherence was assessed
by self-reported attendance. Finally, Knauper et al.
15
exam-
ined the relationship between adhering to self-set dieting
rules and weight loss and concluded that adherence was
associated with weight loss success. In the current analyses of
the A TO Z study, adherence was determined by comparing
the dietary goals of each diet and macronutrient intake data
collected at three post-randomization time points by three
unannounced 24-h recalls per time point, for 181 women.
The 12-month retention rate for the three diet groups
combined was 80% and the total number of 24-h recalls
collected was 2102 for the 181 women, with only 3.2% of
24-h recalls missing. These data allowed for a more extensive
assessment of dietary adherence than previous studies.
In general, absolute adherence to all three dietary guide-
lines was very low. Using the metrics for absolute adherence
established for these analyses, only a single participant in the
Ornish group was absolutely adherent to the guidelines at
all three post-randomization time points. Even after relaxing
the definition of absolute adherence to include being
adherent at two out of the three time points, the numbers
of participants achieving these adherence levels were still
very small. Low adherence rates are a likely indication of the
difficulty involved in closely following dietary weight loss
guidelines from popular diet books. Notably, the participants
in the present cohort had eight class sessions of reviewing
their assigned diet books with a registered dietitian before
they were left to follow the diets on their own for 10 months.
This is more help than the average person would receive who
simply purchased the book and read through the guidelines
completely on their own. Therefore, the adherence levels
observed in this study are likely even higher than in the
-10
-8
-6
-4
-2
0
12-Month Weight Change (kg)
Tertile 1
Tertile 3
P=0.0006 P=0.06P=0.12
Atkins Zone Ornish
Figure 1 Weight loss by tertile of dietary adherence. Mean±s.e. Tertile
1¼most adherent and Tertile 3 ¼least adherent. Statistical testing of
differences between tertiles for each diet group was conducted using t-tests.
Dietary adherence and weight loss success
S Alhassan et al
989
International Journal of Obesity
general population. This suggests that a controlled compar-
ison of the relative impacts of the popular weight loss diets
used in this trial in which participants achieved close to
complete adherence with the different diets would be
possible perhaps only by a feeding study where all meals
were provided to participants. A feeding study would more
effectively address the effect of adherence to weight loss diets
as designed by their respective authors. However, such a
study would have limited external validity since it is clear
that in the real world the typical level of adherence to dietary
weight loss guidelines is quite poor. Despite the generally
low levels of adherence reported in the present study, we
believe these results have more practical public health
relevance than a feeding study because the conditions are
closer to those experienced in the real world.
Despite our extensive dietary data, there were some
limitations in assessing and contrasting adherence for the
diet groups. The assessment of dietary adherence was based
on extensive self-reported 3-day, unannounced, 24-h dietary
recalls. Even though this form of dietary assessment method
is regularly used within the literature; similar to all forms of
self-reported assessment it is therefore limited. It should be
noted that the direct quantification of dietary adherence
would have involved measuring participant’s urinary
ketones, which was not feasible in the present clinical trial.
Adherence level for those assigned to follow the Atkins diet
was determined by the total grams of reported carbohydrate
intake, reflecting the emphasis on carbohydrate restriction
for the Atkins diet. However, given that underreporting of
total daily intake is common in diet assessment,
23
partici-
pants in the Atkins group who underreported carbohydrate
intake would have been assigned an erroneously superior
adherence score. Adherence level for those assigned to follow
the Ornish diet was determined by the total percentage of
calories from fat, proportional to total intake. Underreporting
of total intake would have been relatively less prone to
misclassification in determining adherence to the Ornish
diet than it was for the Atkins diet; misclassification of
adherence for someone in the Ornish group would result
from disproportionate inaccuracies in reporting, which is
less likely, rather than simply underreporting. The Zone
adherence score was the most complex of the three. Rather
than being based on a single macronutrient, the Zone
adherence was based on the combination of proportions of
carbohydrate:fat:protein, with 40:30:30 being the goal for
optimal adherence.
One of the most interesting issues to address in this
exploratory analysis of adherence would have been a
statistical comparison of 100% adherence and 12-month
weight change among the three diets. However, given the
very low number of participants within each diet that were
100% adherent we were unable to carry out this comparison.
Instead, focusing qualitatively on the results in Figure 1, we
report that the differences in weight loss by adherence
score within each diet group were more striking than the
weight loss differences among groups at similar tertiles of
adherence. Our findings would suggest that differences in
dietary macronutrients had only negligible effects on
participants’ weight loss success. Other investigators have
also been able to demonstrate these findings.
24–27
For
example, in a 6-week study examining the effects of two
low-calorie diets (1000 kcal per day) with different macro-
nutrient composition (32% protein, 15% carbohydrate and
53% fat or 29% protein, 45% carbohydrate and 26% fat),
Golay et al.
24
reported no significant difference in the
magnitude of weight loss or changes in body composition
between the two diets. The authors concluded that weight
loss success was due to energy intake and not macronutrient
composition.
If adherence plays an important role in weight loss success,
which is both intuitive and supported by the data presented
here, it would be useful to know who is more likely to be
adherent to a diet. This would allow health care providers to
identify those individuals that might need more assistance
in trying to follow a weight loss program. Several potential
predictors were examined in these analyses, including age,
education level, baseline body weight and baseline percent
body fat. None of these factors were different between the
lowest and the highest tertiles within the diet groups, with
the exception of a higher education level for the more
adherent individuals in the Ornish group. It is likely that
psychosocial characteristics might be predictive of adher-
ence, which warrants further analysis.
The main findings of this weight loss study, presented in a
previous report, indicated that while all three diet groups
lost modest amounts of weight, the Atkins group at 12
months lost approximately twice the weight of the other
groups. The findings presented here indicate that weight loss
in the lowest tertile of adherence was negligible in all three
diet groups, and more pronounced in the highest tertile of
adherence for each diet group. It appears that substantial
differences in proportions of dietary macronutrients play
only a modest role in weight loss success, and that success is
possible on any of these diets provided there is adequate
adherence. Getting individuals to adhere to whatever diet
they choose to follow deserves more emphasis. It remains
to be determined to what extent there is a need for dietary
weight loss programs that are easier to adhere to vs
identifying and addressing individual barriers to adherence,
or both.
Acknowledgements
This investigation was supported by NIH grant R21
AT001098, by a grant from the Community Foundation of
Southeastern Michigan, and by Human Health Service grant
M01-RR00070, General Clinical Research Centers, National
Center for Research Resources and National Institutes of
Health. Dr Gardner received a pilot grant from the Robert
C Atkins Foundation in 2007 after the conclusion of the A
Dietary adherence and weight loss success
S Alhassan et al
990
International Journal of Obesity
TO Z weight loss study. None of the other authors had a
personal or financial conflict of interest.
References
1 Bish CL, Blanck HM, Serdula MK, Marcus M, Kohl III HW, Khan
LK. Diet and physical activity behaviors among Americans trying
to lose weight: 2000 Behavioral Risk Factor Surveillance System.
Obes Res 2005; 13: 596–607.
2 Thom T, Haase N, Rosamond W, Howard VJ, Rumsfeld J, Manolio
Tet al. Heart disease and stroke statisticsF2006 Update: a report
from the American Heart Association Statistics Committee and
Stroke Statistics Subcommittee. Circulation 2006; 113: e85–151.
3 Crawford D, Jeffery RW, French SA. Can anyone successfully
control their weight? Findings of a three year community-based
study of men and women. Int J Obes Relat Metab Disord 2000; 24:
1107–1110.
4 Serdula MK, Mokdad AH, Williamson DF, Galuska DA, Mendlein
JM, Heath GW. Prevalence of attempting weight loss and
strategies for controlling weight. JAMA 1999; 282: 1353–1358.
5 Diabetes Prevention Program Research Group. Reduction in the
incidence of type 2 diabetes with lifestyle intervention or
metformin. N Engl J Med 2002; 346: 393–403.
6 Leon A, Sanchez O. Response of blood lipids to exercise training
alone or combined with dietary intervention. Med Sci Sports Exerc
2001; 33: S502–S515.
7 Tchernof A, Nolan A, Sites CK, Ades PA, Poehlman ET. Weight loss
reduces C-reactive protein levels in obese postmenopausal
women. Circulation 2002; 105: 564–569.
8 Stevens VJ, Obarzanek E, Cook NR, Lee IM, Appel LJ, Smith West
Det al. Long-term weight loss and changes in blood pressure:
results of the trials of hypertension prevention, phase II. Ann Inter
Med 2001; 134:111.
9 Gardner CD, Kiazand A, Alhassan S, Kim S, Stafford RS, Balise RR
et al. Comparison of the Atkins, Zone, Ornish, and LEARN diets
for change in weight and related risk factors among overweight
premenopausal women. The A TO Z Weight Loss Study: a
randomized trial. JAMA 2007; 297: 969–977.
10 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 reduction: a
randomized trial. JAMA 2005; 293: 43–53.
11 Brehm BJ, Seeley RJ, Daniels SR, D0Alessio DA. A randomized trial
comparing a very low carbohydrate diet and a calorie-restricted
low fat diet on body weight and cardiovascular risk factors in
healthy women. J Clin Endocrinol Metab 2003; 88: 1617–1623.
12 Foster GD, Wyatt HR, Hill JO, McGuckin BG, Brill C, Mohammed
BS et al. A randomized trial of a low-carbohydrate diet for obesity.
N Engl J Med 2003; 348: 2082–2090.
13 Stern L, Iqbal N, Seshadri P, Chicano KL, Daily DA, McGrory J
et al. The effects of low-carbohydrate versus conventional weight
loss diets in severely obese adults: one-year follow-up of a
randomized trial. Ann Inter Med 2004; 140: 778–785.
14 Heymsfield SB, Harp JB, Reitman ML, Beetsch JW, Schoeller DA,
Erondu N et al. Why do obese patients not lose more weight
when treated with low-calorie diets? A mechanistic perspective.
Am J Clin Nutr 2007; 85: 346–354.
15 Knauper B, Cheema S, Rabiau M, Borten O. Self-set dieting rules:
adherence and prediction of weight loss success. Appetite 2005;
44: 283–288.
16 Westman EC, Yancy WS, Edman JS, Tomlin KF, Perkins CE. Effect
of 6-month adherence to a very low carbohydrate diet program.
Am J Med 2002; 113: 30.
17 Heshka S, Anderson JW, Atkinson RL, Greenway FL, Hill JO,
Phinney SD et al. Weight loss with self-help compared with a
structured commercial program: a randomized trial. JAMA 2003;
289: 1792–1798.
18 Atkins R. Dr. Atkins’ New Diet Revolution. Harper Collins: New
York, 2002.
19 Sears B, Lawren W. Enter The Zone: A Dietary Road Map to Lose Weight
Permanently: Reset Your Genetic Code: Prevent Disease: Achieve
Maximum Physical Performance. Harper Collins: New York, 1995.
20 Ornish D. Eat More Weigh Less. Harper Collins: New York, 2001.
21 Brownell K. The LEARN Program for Weight Management 10th edn.
American Health Publishing Company: Dallas, 2000.
22 Rencher AC. Characterizing and displaying multivariate data.
Methods of Multivariate Analysis vol. 2. John Wiley: Hoboken, NJ,
2002. pp 43–81.
23 Weber JL, Reid PM, Greaves KA, DeLany JP, Stanford VA, Going SB
et al. Validity of self-reported energy intake in lean and obese
young women, using two nutrient databases, compared with
total energy expenditure assessed by doubly labeled water. Eur J
Clin Nutr 2001; 55: 940–950.
24 Golay A, Allaz AF, Morel Y, de Tonnac N, Tankova S, Reaven G.
Similar weight loss with low- or high-carbohydrate diets. Am J
Clin Nutr 1996; 63: 174–178.
25 Leibel RL, Hirsch J, Appel BE, Checani GC. Energy intake required
to maintain body weight is not affected by wide variation in diet
composition. Am J Clin Nutr 1992; 55: 350–355.
26 Rumpler WV, Seale JL, Miles CW, Bodwell CE. Energy-intake
restriction and diet-composition effects on energy expenditure in
men. Am J Clin Nutr 1991; 53: 430–436.
27 Yang MU, Van Itallie TB. Composition of weight lost during
short-term weight reduction. Metabolic responses of obese
subjects to starvation and low-calorie ketogenic and nonketo-
genic diets. J Clin Invest 1976; 58: 722–730.
Dietary adherence and weight loss success
S Alhassan et al
991
International Journal of Obesity
... However, many individuals lose less weight than expected, thereby negating the potential health benefits of weight loss (eg, reduced cardiovascular disease [CVD] risk and severity) [3,4]. These suboptimal outcomes can be, in part, attributed to nonadherence to the prescribed calorie goal and recommended dietary guidelines to reduce energy intake [5]. Research has shown that dietary lapses (ie, specific instances of nonadherence to BOT dietary goals) occur 3-4 times per week in BOT and are associated with poorer weight losses on average [6,7]. ...
... BOT is a recommended first-line treatment for weight loss and has the potential to reduce the severity of CVD risk factors [1][2][3][4]. However, nonadherence to the prescribed diet in BOT (ie, dietary lapse) has been shown to prevent many individuals from achieving expected weight loss outcomes [5,6]. Although gold standard BOT protocols typically provide behavioral strategies that are intended to promote dietary adherence (eg, stimulus control and meal planning), these interventions do not appropriately account for the complex, momentary, and dynamic nature of the numerous potential triggers of dietary lapses in everyday life [12]. ...
Article
Background Behavioral obesity treatment (BOT) is a gold standard approach to weight loss and reduces the risk of cardiovascular disease. However, frequent lapses from the recommended diet stymie weight loss and prevent individuals from actualizing the health benefits of BOT. There is a need for innovative treatment solutions to improve adherence to the prescribed diet in BOT. Objective The aim of this study is to optimize a smartphone-based just-in-time adaptive intervention (JITAI) that uses daily surveys to assess triggers for dietary lapses and deliver interventions when the risk of lapse is high. A microrandomized trial design will evaluate the efficacy of any interventions (ie, theory-driven or a generic alert to risk) on the proximal outcome of lapses during BOT, compare the effects of theory-driven interventions with generic risk alerts on the proximal outcome of lapse, and examine contextual moderators of interventions. Methods Adults with overweight or obesity and cardiovascular disease risk (n=159) will participate in a 6-month web-based BOT while using the JITAI to prevent dietary lapses. Each time the JITAI detects elevated lapse risk, the participant will be randomized to no intervention, a generic risk alert, or 1 of 4 theory-driven interventions (ie, enhanced education, building self-efficacy, fostering motivation, and improving self-regulation). The primary outcome will be the occurrence of lapse in the 2.5 hours following randomization. Contextual moderators of intervention efficacy will also be explored (eg, location and time of day). The data will inform an optimized JITAI that selects the theory-driven approach most likely to prevent lapses in a given moment. Results The recruitment for the microrandomized trial began on April 19, 2021, and is ongoing. Conclusions This study will optimize a JITAI for dietary lapses so that it empirically tailors the provision of evidence-based intervention to the individual and context. The finalized JITAI will be evaluated for efficacy in a future randomized controlled trial of distal health outcomes (eg, weight loss). Trial Registration ClinicalTrials.gov NCT04784585; http://clinicaltrials.gov/ct2/show/NCT04784585 International Registered Report Identifier (IRRID) DERR1-10.2196/33568
... 4 Adherence to prescribed dietary goals, as measured by doubly labeled water or self-reported food diaries, has been robustly associated with overall rates of weight loss during lifestyle modification interventions. [5][6][7][8][9][10][11][12] Consistent with these findings, research on dietary lapses (i.e., specific instances of nonadherence to one or more of the dietary goals set forth in lifestyle modification interventions) ...
Article
Full-text available
Lapses from the dietary prescription in lifestyle modification interventions for overweight/obesity are common and impact weight loss outcomes. While it is expected that lapses influence weight via increased consumption, there are no studies that have evaluated how dietary lapses affect dietary intake during treatment. This study examined the association between daily lapses and daily energy and macronutrient intake during a lifestyle modification intervention. This study used an intensive longitudinal design to observe participants throughout a 6-month lifestyle modification intervention. Participants (n=32) were adults with overweight/obesity (body mass index 25-50 kg/m²) and a diagnosed cardiovascular disease risk factor (e.g., hypertension) with a desire to lose weight. Participants underwent a gold-standard individual in-person lifestyle modification protocol consisting of 3 months of weekly sessions with 3 months of monthly sessions. Each participant’s dietary prescription included a calorie target range that was based on their starting weight. Participants completed ecological momentary assessment (EMA; repeated daily smartphone surveys) every other week to self-report on dietary lapses and telephone-based 24-hour dietary recalls every 6 weeks. On days with EMA and recalled intake (n=210 days), linear mixed models demonstrated significant associations between daily lapse and higher total daily caloric intake (B= 139.20, p<.05), more daily grams of added sugar (B=16.24, p<.001), and likelihood of exceeding the daily calorie goal (B=0.89, p<.05). The associations between daily lapse and intake of all other daily macronutrients were non-significant. This study contributes to literature suggesting that dietary lapses pose a threat to weight loss success. Results indicate that reducing lapse frequency could reduce overall caloric intake and added sugar consumption. This article is protected by copyright. All rights reserved.
... Exercise and caloric restriction are proposed to exert beneficial effects through natural augmentations of cytoprotective systems through the introduction of a mild stress. An alternative method to induce this stress is via a controlled exposure to other stressors such as heat, cold, or mild irradiation [207][208][209]. While interventions such as caloric restriction and exercise are still problematical for adherence, these even more drastic mild stressors are much less likely to be accepted by a clinical audience. ...
Article
Full-text available
During the aging process our body becomes less well equipped to deal with cellular stress, resulting in an increase in unrepaired damage. This causes varying degrees of impaired functionality and an increased risk of mortality. One of the most effective anti-aging strategies involves interventions that combine simultaneous glucometabolic support with augmented DNA damage protection/repair. Thus, it seems prudent to develop therapeutic strategies that target this combinatorial approach. Studies have shown that the ADP-ribosylation factor (ARF) GTPase activating protein GIT2 (GIT2) acts as a keystone protein in the aging process. GIT2 can control both DNA repair and glucose metabolism. Through in vivo co-regulation analyses it was found that GIT2 forms a close coexpression-based relationship with the relaxin-3 receptor (RXFP3). Cellular RXFP3 expression is directly affected by DNA damage and oxidative stress. Overexpression or stimulation of this receptor, by its endogenous ligand relaxin 3 (RLN3), can regulate the DNA damage response and repair processes. Interestingly, RLN3 is an insulin-like peptide and has been shown to control multiple disease processes linked to aging mechanisms, e.g., anxiety, depression, memory dysfunction, appetite, and anti-apoptotic mechanisms. Here we discuss the molecular mechanisms underlying the various roles of RXFP3/RLN3 signaling in aging and age-related disorders.
... As we have recently discussed, it is common for participants to have difficulty achieving prescribed research diets in a free-living setting, which makes reporting the actual dietary intake and assessing adherence critical for interpretation [2]. Greater dietary adherence, regardless of the type of diet, is an important factor in weight-loss success and maintenance [3][4][5]. We recently conducted an intervention trial comparing a lowcarbohydrate (ketogenic) and a Mediterranean diet in which we published a separate methods and adherence paper [6]. ...
Article
Current guidelines for obesity treatment recommend reducing daily caloric intake for weight loss. However, long-term weight loss continues to be an issue in obesity management. Alternative weight loss strategies have increased in popularity, such as intermittent energy restriction (IER), a type of eating pattern with periods of fasting alternating with unrestricted eating. The effects of IER on weight loss, cardiovascular risk factors, inflammation, and appetite are not clear. The purpose of this systematic review was to analyze short- (<24 weeks) and long-term (≥24 weeks) effects of IER on anthropometric, cardiometabolic, inflammatory, and appetite outcomes in adults with overweight/obesity. PubMed, CINAHL, Embase, and PsycInfo were searched from inception to July 2020. Human randomized controlled trials (RCTs) on IER with participants with a body mass index ≥25 kg/m ² were included in this review. A total of 42 articles (reporting on 27 different RCTs) were included. In short-term studies, IER showed pre-to-post treatment improvements in eight of nine studies that assessed weight. Weight outcomes were sustained in the long-term. However, no significant long-term between group differences were observed in fat mass, other anthropometric, cardiometabolic, inflammatory, or appetite outcomes. Compared to continuous energy restriction (CER), IER showed no significant long-term differences in anthropometric, cardiometabolic, inflammatory, or appetite outcomes in included studies. More long-term studies are needed to assess the benefits of IER on health outcomes.
Article
Dietary restriction of carbohydrate has been demonstrated to be beneficial for nervous system dysfunction in animal models and may be beneficial for human chronic pain. The purpose of this review is to assess the impact of a low-carbohydrate/ketogenic diet on the adult nervous system function and inflammatory biomarkers to inform nutritional research for chronic pain. An electronic data base search was carried out in May 2021. Publications were screened for prospective research with dietary carbohydrate intake <130g/day and duration of ≥2 weeks. Studies were categorised into those reporting adult neurological outcomes to be extracted for analysis and those reporting other adult research outcomes Both groups were screened again for reported inflammatory biomarkers. From 1548 studies there were 847 studies included. Sixty-four reported neurological outcomes with 83% showing improvement. Five hundred and twenty-three studies had a different research focus (metabolic n=394, sport/performance n=51, cancer n=33, general n=30, neurological with non-neuro outcomes n=12, or gastrointestinal n=4). The second screen identified 63 studies reporting on inflammatory biomarkers with 71% reporting a reduction in inflammation. The overall results suggest a favourable outcome on the nervous system and inflammatory biomarkers from a reduction in dietary carbohydrates. Both nervous system sensitisation and inflammation occur in chronic pain and the results from this review indicate it may be improved by low-carbohydrate nutritional therapy. More clinical trials within this population are required to build on the few human trials that have been done.
Chapter
In individuals with overweight or obesity, maintenance of moderate weight loss (5–10% of initial body weight) improves metabolic health and reduces disease risk. This article provides a definition of weight loss maintenance and examines current research on successful weight loss maintenance. The physiological, psychological, and environmental determinants that make maintenance challenging are discussed, and diet, physical activity, and behavioral strategies that support weight loss maintenance are also reviewed. The article closes with recommendations for achieving weight loss maintenance, as well as directions for future research.
Article
Objective: To assess the effects of the COVID-19 pandemic on weight loss, physical activity (PA), and sleep in adults with overweight/obesity participating in a 39-week weight loss intervention. Methods: Participants (n=81, 85% female, mean±SD 38.0±7.8 years, BMI 34.1±5.7 kg/m2) were enrolled in 3 separate cohorts. Cohorts 1 and 2 were studied prior to the pandemic ("pre-COVID cohorts"). Cohort 3 ("COVID cohort") transitioned to a virtual intervention at week 6 when "stay-at-home" orders was implemented in Colorado. Weight was assessed at baseline, week 12, and week 39 with clinic scales before the pandemic, and home scales during the pandemic. Diet was assessed with Likert scales at weeks 4, 8 and 12. PA and sleep were assessed at baseline and week 12 with actigraphy. Results: Participants in the COVID cohort reported greater dietary adherence (p=0.004) and lost more weight than those in the pre-COVID cohorts at week 12 (-7.7±3.3 kg vs. -3.7±3.0 kg, p<0.001) and 39 (-8.5±4.4 kg vs. -2.8±4.6 kg, p<0.001). Energy intake did not differ between cohorts (p=0.51). The COVID cohort increased both sedentary time while awake and time-in-bed at night. Conclusions: Although the pandemic caused disruptions for the COVID cohort, participants still achieved weight loss with continued behavioral support.
Article
Full-text available
Background: Debates on effective and safe diets for managing obesity in adults are ongoing. Low-carbohydrate weight-reducing diets (also known as 'low-carb diets') continue to be widely promoted, marketed and commercialised as being more effective for weight loss, and healthier, than 'balanced'-carbohydrate weight-reducing diets. Objectives: To compare the effects of low-carbohydrate weight-reducing diets to weight-reducing diets with balanced ranges of carbohydrates, in relation to changes in weight and cardiovascular risk, in overweight and obese adults without and with type 2 diabetes mellitus (T2DM). Search methods: We searched MEDLINE (PubMed), Embase (Ovid), the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science Core Collection (Clarivate Analytics), ClinicalTrials.gov and WHO International Clinical Trials Registry Platform (ICTRP) up to 25 June 2021, and screened reference lists of included trials and relevant systematic reviews. Language or publication restrictions were not applied. Selection criteria: We included randomised controlled trials (RCTs) in adults (18 years+) who were overweight or living with obesity, without or with T2DM, and without or with cardiovascular conditions or risk factors. Trials had to compare low-carbohydrate weight-reducing diets to balanced-carbohydrate (45% to 65% of total energy (TE)) weight-reducing diets, have a weight-reducing phase of 2 weeks or longer and be explicitly implemented for the primary purpose of reducing weight, with or without advice to restrict energy intake. DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles and abstracts and full-text articles to determine eligibility; and independently extracted data, assessed risk of bias using RoB 2 and assessed the certainty of the evidence using GRADE. We stratified analyses by participants without and with T2DM, and by diets with weight-reducing phases only and those with weight-reducing phases followed by weight-maintenance phases. Primary outcomes were change in body weight (kg) and the number of participants per group with weight loss of at least 5%, assessed at short- (three months to < 12 months) and long-term (≥ 12 months) follow-up. Main results: We included 61 parallel-arm RCTs that randomised 6925 participants to either low-carbohydrate or balanced-carbohydrate weight-reducing diets. All trials were conducted in high-income countries except for one in China. Most participants (n = 5118 randomised) did not have T2DM. Mean baseline weight across trials was 95 kg (range 66 to 132 kg). Participants with T2DM were older (mean 57 years, range 50 to 65) than those without T2DM (mean 45 years, range 22 to 62). Most trials included men and women (42/61; 3/19 men only; 16/19 women only), and people without baseline cardiovascular conditions, risk factors or events (36/61). Mean baseline diastolic blood pressure (DBP) and low-density lipoprotein (LDL) cholesterol across trials were within normal ranges. The longest weight-reducing phase of diets was two years in participants without and with T2DM. Evidence from studies with weight-reducing phases followed by weight-maintenance phases was limited. Most trials investigated low-carbohydrate diets (> 50 g to 150 g per day or < 45% of TE; n = 42), followed by very low (≤ 50 g per day or < 10% of TE; n = 14), and then incremental increases from very low to low (n = 5). The most common diets compared were low-carbohydrate, balanced-fat (20 to 35% of TE) and high-protein (> 20% of TE) treatment diets versus control diets balanced for the three macronutrients (24/61). In most trials (45/61) the energy prescription or approach used to restrict energy intake was similar in both groups. We assessed the overall risk of bias of outcomes across trials as predominantly high, mostly from bias due to missing outcome data. Using GRADE, we assessed the certainty of evidence as moderate to very low across outcomes. Participants without and with T2DM lost weight when following weight-reducing phases of both diets at the short (range: 12.2 to 0.33 kg) and long term (range: 13.1 to 1.7 kg). In overweight and obese participants without T2DM: low-carbohydrate weight-reducing diets compared to balanced-carbohydrate weight-reducing diets (weight-reducing phases only) probably result in little to no difference in change in body weight over three to 8.5 months (mean difference (MD) -1.07 kg, (95% confidence interval (CI) -1.55 to -0.59, I2 = 51%, 3286 participants, 37 RCTs, moderate-certainty evidence) and over one to two years (MD -0.93 kg, 95% CI -1.81 to -0.04, I2 = 40%, 1805 participants, 14 RCTs, moderate-certainty evidence); as well as change in DBP and LDL cholesterol over one to two years. The evidence is very uncertain about whether there is a difference in the number of participants per group with weight loss of at least 5% at one year (risk ratio (RR) 1.11, 95% CI 0.94 to 1.31, I2 = 17%, 137 participants, 2 RCTs, very low-certainty evidence). In overweight and obese participants with T2DM: low-carbohydrate weight-reducing diets compared to balanced-carbohydrate weight-reducing diets (weight-reducing phases only) probably result in little to no difference in change in body weight over three to six months (MD -1.26 kg, 95% CI -2.44 to -0.09, I2 = 47%, 1114 participants, 14 RCTs, moderate-certainty evidence) and over one to two years (MD -0.33 kg, 95% CI -2.13 to 1.46, I2 = 10%, 813 participants, 7 RCTs, moderate-certainty evidence); as well in change in DBP, HbA1c and LDL cholesterol over 1 to 2 years. The evidence is very uncertain about whether there is a difference in the number of participants per group with weight loss of at least 5% at one to two years (RR 0.90, 95% CI 0.68 to 1.20, I2 = 0%, 106 participants, 2 RCTs, very low-certainty evidence). Evidence on participant-reported adverse effects was limited, and we could not draw any conclusions about these. AUTHORS' CONCLUSIONS: There is probably little to no difference in weight reduction and changes in cardiovascular risk factors up to two years' follow-up, when overweight and obese participants without and with T2DM are randomised to either low-carbohydrate or balanced-carbohydrate weight-reducing diets.
Article
Objective : With the global rise in obesity and the metabolic syndrome, double diabetes is increasingly prevalent in patients with type 1 diabetes. This review investigated the impact of diet on weight management and metabolic outcomes in patients with double diabetes. Research Methods & Procedures : MEDLINE, CENTRAL, EMBASE, PsycINFO, CINAHL, ERIC and Web of Science databases were searched until September 2020. Population or individual-level dietary interventions, and observational studies investigating dietary patterns in adults with type 1 diabetes and overweight or obesity were eligible for inclusion. The quality of studies was assessed. Results : Four eligible studies were included in this review, comprising two randomised controlled trials, one pretest-posttest study and one cross-sectional study. Study populations included between 10 and 1040 participants. Dietary interventions included the Mediterranean diet, low-fat diet, intermittent fasting, continuous energy restriction and a combination of fasting and a standardised low-calorie diabetic diet (LCD). Significant weight loss was observed within groups for low-fat diet, Mediterranean diet, fasting, LCD with fasting, intermittent fasting, or continuous energy restriction, but there were no between-group differences. Weight maintenance was only achieved in interventions where fasting or intermittent fasting were present. Dietary interventions in published data failed to demonstrate effects on metabolic syndrome. Conclusions : Larger sample, high-quality trials conducted over longer periods are urgently required to determine the efficacy of diet for weight management and improving metabolic outcomes in individuals with double diabetes. This would provide much needed evidence-based guidance for dietary interventions, which are well known to be the cornerstone of clinical care.
Article
Full-text available
Overweight and obesity are increasing in the United States. Changes in diet and physical activity are important for weight control. To examine the prevalence of attempting to lose or to maintain weight and to describe weight control strategies among US adults. The Behavioral Risk Factor Surveillance System, a random-digit telephone survey conducted in 1996 by state health departments. Setting The 49 states (and the District of Columbia) that participated in the survey. Adults aged 18 years and older (N = 107 804). Reported current weights and goal weights, prevalence of weight loss or maintenance attempts, and strategies used to control weight (eating fewer calories, eating less fat, or using physical activity) by population subgroup. The prevalence of attempting to lose and maintain weight was 28.8% and 35.1 % among men and 43.6% and 34.4% among women, respectively. Among those attempting to lose weight, a common strategy was to consume less fat but not fewer calories (34.9% of men and 40.0% of women); only 21.5% of men and 19.4% of women reported using the recommended combination of eating fewer calories and engaging in at least 150 minutes of leisure-time physical activity per week. Among men trying to lose weight, the median weight was 90.4 kg with a goal weight of 81.4 kg. Among women, the median weight was 70.3 kg with a goal weight of 59.0 kg. Weight loss and weight maintenance are common concerns for US men and women. Most persons trying to lose weight are not using the recommended combination of reducing calorie intake and engaging in leisure-time physical activity 150 minutes or more per week.
Article
Background: A previous paper reported the 6-month comparison of weight loss and metabolic changes in obese adults randomly assigned to either a low-carbohydrate diet or a conventional weight loss diet. Objective: To review the 1-year outcomes between these diets. Design: Randomized trial. Setting: Philadelphia Veterans Affairs Medical Center. Participants: 132 obese adults with a body mass index of 35 kg/m 2 or greater; 83% had diabetes or the metabolic syndrome. Intervention: Participants received counseling to either restrict carbohydrate intake to <30 g per day (low-carbohydrate diet) or to restrict caloric intake by 500 calories per day with <30% of calories from fat (conventional diet). Measurements: Changes in weight, lipid levels, glycemic control, and insulin sensitivity. Results: By 1 year, mean (±SD) weight change for persons on the low-carbohydrate diet was -5.1 ± 8.7 kg compared with -3.1 ± 8.4 kg for persons on the conventional diet. Differences between groups were not significant (-1.9 kg [95% Cl, -4.9 to 1.0 kg]; P = 0.20). For persons on the low-carbohydrate diet, triglyceride levels decreased more (P = 0.044) and high-density lipoprotein cholesterol levels decreased less (P = 0.025). As seen in the small group of persons with diabetes (n = 54) and after adjustment for covariates, hemoglobin A 1c levels improved more for persons on the low-carbohydrate diet These more favorable metabolic responses to a low-carbohydrate diet remained significant after adjustment for weight loss differences. Changes in other lipids or insulin sensitivity did not differ between groups. Limitations: These findings are limited by a high dropout rate (34%) and by suboptimal dietary adherence of the enrolled persons. Conclusion: Participants on a low-carbohydrate diet had more favorable overall outcomes at 1 year than did those on a conventional diet. Weight loss was similar between groups, but effects on atherogenic dyslipidemia and glycemic control were still more favorable with a low-carbohydrate diet after adjustment for differences in weight loss.
Article
Background: Weight loss appears to be an effective method for primary prevention of hypertension. However, the long-term effects of weight loss on blood pressure have not been extensively studied. Objective: To present detailed results from the weight loss arm of Trials of Hypertension Prevention (TOHP) II. Design: Multicenter, randomized clinical trial testing the efficacy of lifestyle interventions for reducing blood pressure over 3 to 4 years. Participants in TOHP II were randomly assigned to one of four groups. This report focuses only on participants assigned to the weight loss (n = 595) and usual care control (n = 596) groups. Patients: Men and women 30 to 54 years of age who had nonmedicated diastolic blood pressure of 83 to 89 mm Hg and systolic blood pressure less than 140 mm Hg and were 110% to 165% of their ideal body weight at baseline. Intervention: The weight loss intervention included a 3-year program of group meetings and individual counseling focused on dietary change, physical activity, and social support. Measurements: Weight and blood pressure data were collected every 6 months by staff who were blinded to treatment assignment Results: Mean weight change from baseline in the intervention group was -4.4 kg at 6 months, -2.0 kg at 18 months, and -0.2 kg at 36 months. Mean weight change in the control group at the same time points was 0.1, 0.7, and 1.8 kg. Blood pressure was significantly lower in the intervention group than in the control group at 6, 18, and 36 months. The risk ratio for hypertension in the intervention group was 0.58 (95% Cl, 0.36 to 0.94) at 6 months, 0.78 (Cl, 0.62 to 1.00) at 18 months, and 0.81 (Cl, 0.70 to 0.95) at 36 months. In subgroup analyses, intervention participants who lost at least 4.5 kg at 6 months and maintained this weight reduction for the next 30 months had the greatest reduction in blood pressure and a relative risk for hypertension of 0.35 (Cl, 0.20 to 0.59). Conclusions: Clinically significant long-term reductions in blood pressure and reduced risk for hypertension can be achieved with even modest weight loss.
Article
PURPOSE: The purpose of this study is to review the effects of aerobic exercise training (AET) on blood lipids and assess dose-response relationships and diet interactions. METHODS: We reviewed papers published over the past three decades pertaining to intervention trials on the effects of > or = 12 wk of AET on blood lipids and lipoprotein outcomes in adult men and women. Included were studies with simultaneous dietary and AET interventions, if they had appropriate comparison groups. Studies were classified by the participants' relative weights expressed as mean BMIs. Information was extracted on baseline characteristics of study subjects, including age, sex, and relative baseline cholesterol levels; details on the training programs; and the responses to training of body weight, VO(2max), and blood total cholesterol (TC) and low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C), and triglyceride (TG). RESULTS: We identified 51 studies, 28 of which were randomized controlled trials. AET was generally performed at a moderate to hard intensity, with weekly energy expenditures ranging from 2,090 to >20,000 kJ. A marked inconsistency was observed in responsiveness of blood lipids. The most commonly observed change was an increase in HDL-C (with reductions in TC, LDL-C, and TG less frequently observed). Insufficient data are available to establish dose-response relationships between exercise intensity and volume with lipid changes. The increase in HDL-C with AET was inversely associated with its baseline level (r = -0.462), but no significant associations were found with age, sex, weekly volume of exercise, or with exercise-induced changes in body weight or VO(2max). CONCLUSION: Moderate- to hard-intensity AET inconsistently results in an improvement in the blood lipid profile, with the data insufficient to establish dose-response relationships.
Article
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 reduction. 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, respectively). 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.
Article
The effects of starvation, an 800-kcal mixed diet and an 800-kcal ketogenic (low carbohydrate-high fat) diet on the composition of weight lost were determined in each of six obese subjects during three 10-day periods. The energy-nitrogen balance method was used to quantify the three measurable components of weight loss; protein, fat, and water. On the 800-kcal ketogenic diet, subjects lost (mean +/- SE) 466.6 +/-51.3 g/day; on the isocaloric mixed diet, which provided carbohydrate and fat in conventional proportions, they lost 277.9+/- 32.1 g/day. Composition of weight lost (percentage) during the ketogenic diet was water 61.2, fat 35.0, protein 3.8. During the mixed diet, composition of loss was water 37.1, fat 59.5, protein 3.4...