Telehealth dietary interventions improve diet quality in chronic disease

Telehealth methods to deliver dietary interventions in adults
with
chronic disease: a systematic review and meta-analysis1,2
Jaimon T Kelly,3 Dianne P Reidlinger,3 Tammy C Hoffmann,4
and Katrina L Campbell3,5*
3
Faculty of Health Sciences and Medicine,
4
Centre for Research in Evidence Based Practice, Bond
University, Gold Coast, Australia; and
5
Nutrition and
Dietetics Department, Princess Alexandra Hospital, Brisbane,
Australia
ABSTRACT
Background: The long-term management of chronic disease re-
quires the adoption of complex dietary recommendations, which
can be facilitated by regular coaching to support behavioral
changes.
Telehealth interventions can overcome patient-centered barriers
to
accessing face-to-face programs and provide feasible delivery
methods,

accessible regardless of geographic location.
Objective: This systematic review assessed the effectiveness of
telehealth dietary interventions at facilitating dietary change in
chronic disease.
Design: A structured systematic search was conducted for all
ran-
domized controlled trials evaluating multifactorial dietary
interven-
tions in adults with chronic disease that provided diet education
in
an intervention longer than 4 wk. Meta-analyses that used the
ran-
dom-effects model were performed on diet quality, dietary
adher-
ence, fruit and vegetables, sodium intake, energy, and dietary
fat
intake.
Results: A total of 25 studies were included, involving 7384
participants. The telehealth dietary intervention was effec-
tive at improving diet quality [standardized mean difference
(SMD): 0.22 (95% CI: 0.09, 0.34), P = 0.0007], fruit and veg-
etable intake [mean difference (MD) 1.04 servings/d (95% CI:
0.46, 1.62 servings/d), P = 0.0004], and dietary sodium intake
[SMD: 20.39 (20.58, 20.20), P = 0.0001]. Single nutrients
(total fat and energy consumption) were not improved by tele-

health intervention; however, after a telehealth intervention,
impor-
tant clinical outcomes were improved, such as systolic blood
pressure
[MD: 22.97 mm Hg (95% CI: 25.72, 20.22 mm Hg), P = 0.05],
total cholesterol [MD: 20.08 mmol/L (95% CI: 20.16, 20.00
mmol/L),
P = 0.04], triglycerides [MD: 20.10 mmol/L (95% CI: 20.19,
20.01 mmol/L), P = 0.04], weight [MD: 20.80 kg (95% CI:
21.61, 0 kg), P = 0.05], and waist circumference [MD: 22.08 cm
(95% CI: 23.97, 20.20 cm), P = 0.03].
Conclusions: Telehealth-delivered dietary interventions
targeting
whole foods and/or dietary patterns can improve diet quality,
fruit
and vegetable intake, and dietary sodium intake. When
applicable,
they should be incorporated into health care services for people
with
chronic conditions. This review was registered at
http://www.crd.
york.ac.uk/PROSPERO/ as CRD42015026398. Am J Clin Nutr
2016;104:1693–702.
Keywords: telehealth, diet quality, dietary, diet, fruit,
vegetables,
chronic disease
INTRODUCTION

Chronic diseases are the leading cause of ill health, accounting
for .68% of all deaths worldwide (1). Chronic diseases are
characterized by a multifactorial etiology (1), including obesity,
heart disease, diabetes mellitus, hypertension, stroke, and renal
disease, which is often diet related (2). Self-management and
the
adoption of a healthy lifestyle, such as improved dietary habits,
increased physical activity, and other health-related behaviors
(e.g., smoking cessation) are considered essential for the man-
agement of chronic diseases (3, 4). Standard chronic disease
care models, however, are followed by only a minority of pa-
tients for many reasons, including poor compliance and high
patient burden (5). This suggests that the long-term maintenance
of dietary behaviors cannot be facilitated with traditional
models
of care.
Individuals with multiple risk factors for cardiovascular dis-
ease (CVD)6 and other chronic diseases have been identified as
having higher levels of nonattendance in face-to-face (FTF)
consultations (6, 7). Patient-centered barriers, including limited
transport and geographical isolation, working hours, and for-
getting about appointments, can contribute to appointment
nonattendance (8). Additional health care barriers that can hin-
der access to traditional FTF care include administrative error,
poor access to clinic facilities, limited parking, and unfavorable
operating hours of clinics (7).
Telehealth technologies can be used to provide education and
self-management support to facilitate and sustain lifestyle
changes and have several advantages over traditional FTF
models
1
The authors reported no funding received for this study. JTK is

supported
by an Australian Post Graduate Award scholarship through
Bond University.
2 Supplemental Figures 1 and 2 and Supplemental Tables 1–3
are available
from the “Online Supporting Material” link in the online
posting of the
article and from the same link in the online table of contents at
http://ajcn.
nutrition.org.
*To whom correspondence should be addressed. E-mail:
[email protected]
edu.au.
Received April 11, 2016. Accepted for publication October 4,
2016.
First published online November 9, 2016; doi:
10.3945/ajcn.116.136333.
6
Abbreviations used: BP, blood pressure; CVD, cardiovascular
disease;
DBP, diastolic blood pressure; FTF, face-to-face; HbA1c,
glycated hemoglo-
bin; HF, heart failure; MD, mean difference; RCT, randomized
controlled
trial; SBP, systolic blood pressure; SMD, standardized mean

difference;
TIDieR, Template for Intervention Description and Replication.
Am J Clin Nutr 2016;104:1693–702. Printed in USA. � 2016
American Society for Nutrition 1693
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36333.DCSupplemental.html
http://ajcn.nutrition.org/content/suppl/2016/11/09/ajcn.116.1
Supplemental Material can be found at:
http://ajcn.nutrition.org/

of care (9). Telehealth strategies may assist patients with
chronic
disease to achieve dietary behavioral change (9–11) and are
flexible in time and location, with the potential to offer
intensive
interventions that may not be feasible with traditional care
models. According to the WHO (12), telehealth refers to the
delivery of health care services from a distance synchronously
(i.e., same time, different location) and/or asynchronously
(i.e., different time, different location), by use of information
and communication technologies to exchange health in-
formation (12). A telehealth lifestyle intervention may offer
flexibility in delivery mode involving the provision of health
education or counseling individuals or groups remotely via the
telephone (13), computer or Internet (14–16), video (17), e-mail
(18), and/or mobile applications, including text and photo
messaging (19, 20).
Although a number of systematic reviews have covered different
combinations of telehealth interventions in healthy (21–23) and
chronic disease (24–27) populations, none have specifically
evaluated interventions that attempt to change dietary patterns
or
target multiple dietary changes simultaneously (e.g., multiple
food groups, nutrients). These diet interventions represent the
dietary advice that is typically provided to chronic disease pop-
ulations (28). This systematic review, therefore, aimed to assess
the overall effectiveness of telehealth dietary interventions for
facilitating multifactorial dietary change in adults with chronic
disease.
METHODS

We followed a prespecified review protocol, published
elsewhere (29), that detailed our rationale, purpose, and
methodology. It was prospectively registered in the In-
ternational Prospective Register of Systematic Reviews as
CRD42015026398.
Literature search
We performed a literature search in the electronic databases
MEDLINE (http://www.ovid.com), EMBASE
(http://www.embase.
com), CINAHL (https://www.ebscohost.com), and PsychINFO
(http://www.ovid.com) (from inception to November 2015) us-
ing a variety of subject headings and free text terms and syno-
nyms relevant to the review in consultation with an experienced
systematic review search librarian, and published in the
protocol
(29). There was no date or language restriction in our search
strategy. A multistep search approach was taken to retrieve
relevant studies through use of forward-and-backward citation
searching; expert correspondence; search of conference
abstracts,
theses, and dissertations (ProQuest); and the International
Clinical
Trials Register search portal and clinicaltrials.gov to identify
ongoing trials. This review follows the format recommended in
the Preferred Reporting Items for Systematic Reviews and
Meta-Analysis statement (30). Two review authors screened
articles independently, with disagreements in judgment re-
solved by consensus or a third reviewer.
Study selection
All of the search results were merged into EndNote (Thomson
Reuters) and deduplicated before screening. Studies were in-
cluded in the review if they met all of the following criteria:

1) randomized controlled trial (RCT), cluster RCT, or quasi-
RCT;
2) adult participants (.18 y); 3) conducted in a population with
an established diet-related chronic disease defined as obesity
[BMI (in kg/m
2
) $30], diabetes mellitus, heart disease, hyper-
tension, stroke, or kidney disease (29, 31); 4) provision of mul-
tifactorial dietary education in which the dose of total
intervention
contact hours and/or the total number of interaction contacts
was
$50% delivered by $1 telehealth strategy; 5) developed or de-
livered by a qualified health care professional (e.g., nurse, di-
etitian, physician); and 6) reported on any measure of dietary
intake at baseline and $4 wk later at follow-up.
We defined a multifactorial dietary intervention as targeting
more than a singular nutrient and/or food group. Multifactorial
dietary interventions included those aimed at overall diet
quality
(assessed as any outcome that objectively scores adherence to
dietary guidelines) (32–34) and patterns, such as the Mediter-
ranean diet (35) and/or the Dietary Approaches to Stop Hyper-
tension diet (36), or those that educate patients about $2 dietary
components (nutrients and/or food groups) simultaneously.
Studies that targeted $2 diet changes within the same nutrient
(e.g., manipulation of categories of fatty acids) were excluded
because the dietary components related to only 1 nutrient, and
thus were not classified as multifactorial.
Studies were included if they compared a telehealth in-
tervention to usual care (as defined by the trial authors); to

dietary
education in a FTF or group-based environment with no tele-
health component; or via methods for which ,50% of the
intervention was delivered by telehealth; or to a nondietary-
focused intervention.
The primary outcome was dietary intake (any measure), with
secondary outcomes relating to clinical outcomes such as all-
cause mortality, cardiovascular mortality, hospitalizations, and
clinical markers of chronic disease progression [e.g., blood
pressure (BP), weight, blood lipid profiles].
Data extraction and management
The following data were extracted from included studies: in-
tervention details [following the components outlined in the
Template for Intervention Description and Replication (TIDieR)
checklist] (37), participant characteristic (chronic disease, age,
and
sex), attrition, sample size, and study design and duration. Risk
of
bias was assessed by 2 review authors independently by use of
Cochrane methodology (38) to categorize selection bias, perfor-
mance bias, detection bias, attrition bias, and reporting bias in
each
study as low, unclear, or high risk of bias. Means, SDs, SEs, or
95%
CIs for all prespecified primary and secondary outcome data
that
were reported at baseline and follow-up were extracted for
analysis. When a study presented adjusted and unadjusted
values,
the most adjusted value was extracted for analysis.
Statistical analysis

To calculate the overall treatment effect on primary and
secondary outcomes, the difference between the intervention
and
comparison groups’ change scores from baseline to the end of
follow-up was extracted. If change from baseline values was not
available, then end-of-intervention values were extracted, with
the assumption that the baseline values were similar. The vari-
ance was calculated from the SD or SE from the difference
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http://www.ovid.com
http://www.embase.com
http://www.embase.com
https://www.ebscohost.com

http://www.ovid.com
between baseline and follow-up, or from the CI when these
values were not available (38). When interventions and associ-
ated outcomes were assessed as sufficiently homogeneous and
when sufficient information was available from the studies,
quantitative data were pooled into Revman (version 5.3; Co-
chrane Collaboration) for meta-analysis through use of the
DerSimonian-Laird random-effects model (39) and checked
with the fixed-effects model to ensure robustness and suscepti-
bility to potential outliers. The I2 statistic was used to assess
the
inconsistencies between studies and describe the percentage of
variability in effect. Heterogeneity was considered substantial if
the I2 statistic was $50%.
Effect sizes (for combined fruit and vegetable servings, energy
intake, blood pressure, weight, and lipid profiles) were
converted to
standard units and calculated as mean differences (MDs). Effect
sizes for diet quality scores, dietary adherence, sources of
dietary
fat, and sources of dietary sodium intake were calculated as
standardized MDs (SMDs) because of the variability in outcome
measures. We imputed missing SDs for 1 study in the dietary
sodium and systolic BP (SBP) analysis (40) with data from an
included study that used similar methods and sample sizes (41,
42),
as recommended (43). Egger’s plot was explored to assess po-
tential publication bias. Sensitivity analyses were conducted to
investigate study results that appeared to be heterogeneous from
the results of other analyzed studies, including large studies and
high-risk-of-bias studies. Subgroup analyses also were
conducted

on different chronic health conditions (e.g., diabetes mellitus,
CVD); studies that used different telehealth strategies; studies
that
targeted specified single food groups or nutrients (e.g.,
modifying
sodium, fat, fruit, and/or vegetable interventions) compared
with
dietary patterns, and multiple lifestyle education interventions
compared with solely dietary education interventions.
RESULTS
Characteristics of included studies
The flow of study identification and selection is detailed in the
Preferred Reporting Items for Systematic Reviews and Meta-
Analysis flowchart (Supplemental Figure 1). The search identi-
fied 6967 studies. After duplicates were removed and
nonrelevant
studies (n = 5608) were excluded, 370 studies were subject to
full
text review. After this, 345 studies were excluded, leaving 25
for
inclusion, involving 7384 participants. Supplemental Table 1
details the characteristics of the included studies, including the
frequency of contact, delivery provider, and type of dietary edu-
cation. In all but 4 studies (42, 44–46), dietary education was
delivered as part of a multifactorial lifestyle intervention.
Studies
were conducted in CVD (15 studies) (40–42, 46–57), diabetes
mellitus (5 studies) (44, 58–61), end-stage kidney disease (2
studies)
(45, 62), obesity (1 study) (14), and a mix of CVD and diabetes
mellitus (2 studies) (13, 63). The duration of studies ranged
from
8 wk (46, 48, 56) to 8 y (61). Telehealth delivery methods

varied
from the telephone (13 studies) (13, 40–42, 48, 50, 54, 56, 57,
59,
61–63), short message service (4 studies) (45, 49, 51, 58), the
Internet (3 studies) (14, 53, 55), video (1 study) (47) or video-
conferencing (1 study) (60), and a mix of telehealth methods
(3 studies) (44, 46, 50). The percentage of the interventions de-
livered by telehealth methods varied from 66% to 100% across
the included studies.
All of the included studies reported measures of dietary intake
at baseline and follow-up. Studies varied in dietary outcome
measures used and included diet quality (3 studies), dietary
adherence (7 studies), energy intake (3 studies), measures of
dietary fat (8 studies), dietary sodium (7 studies), and intake of
fruits and/or vegetables (9 studies). We were unable to statisti-
cally pool 10 studies into the meta-analysis, and these are
therefore presented narratively (Supplemental Table 2). A table
of excluded dietary studies that did not report dietary outcomes
are provided in Supplemental Table 3.
Effect of telehealth interventions on dietary change
Diet quality
Three studies involving 992 participants measured diet quality
(40, 41, 59) through the use of a diet quality score (40), the
Australian Healthy Eating Index (59), and the Dietary Ap-
proaches to Stop Hypertension diet score (41). The telehealth
intervention improved diet quality [SMD: 0.22 (95% CI: 0.09,
0.34), P = 0.0007, I2 = 0%] compared with nontelehealth
comparators (Figure 1). The results remained significant in
2 trials with 12- (40) and 24- (59) mo follow-up [SMD: 0.18
(95% CI: 0.02, 0.33), P = 0.02, I2 = 0%].
Diet adherence

Dietary adherence outcomes (7 studies) (45, 48, 52, 56, 58, 60,
62) could not be pooled into the meta-analysis because of the
variation in outcome reporting statistics, which could not be
standardized, and therefore are presented narratively in Supple-
mental Table 2. Overall, telehealth intervention substantially
im-
proved diet adherence compared with nontelehealth
comparators,
as reported by the trial authors in 57% (n = 4) of the studies.
Fruit and vegetable intake
A total of 9 studies reported on fruit and vegetable intake (13,
14, 44, 46, 49–51, 53, 54). Telehealth interventions increased
fruit and vegetable intake by 1.04 servings/d [(95% CI: 0.46,
1.62 servings/d), P = 0.009, I2 = 70%] in 4 studies with 5
comparisons (2147 participants), and by 2.94 servings/wk [(95%
CI: 0.91, 4.97 servings/wk), P = 0.005, I2 = 84%] in 2 studies
with 4 comparisons (1682 participants) (Figure 2). Three studies
could not be pooled statistically and are reported in
Supplemental
Table 2. The trial with longer-term 12-mo (13) follow-up sup-
ported this finding [MD: 0.65 (95% CI: 0.02, 1.28), P = 0.04].
In the per-day analysis, 4 of the 5 comparisons used the tele-
phone and 1 used the Internet (14); a sensitivity analysis
showed
that telephone telehealth intervention resulted in increased
fruit and vegetable intake by 0.77 servings/d [(95% CI: 0.39,
1.14),
P = 0.0001], with heterogeneity reduced (I
2
= 35%) in the 4 com-

parisons (2057 participants). The dose of intervention showed
that
weekly contact led to a higher intake [MD: 1.32 servings/d
(95%
CI: 0.38, 2.26 servings/d), P = 0.006, I
2
= 85%] in 3 studies (46,
50, 53) than did monthly contact [MD: 0.27 servings/d (95% CI:
0.02, 0.52 servings/d), P = 0.03, I2 = 0%] (13, 44). The trial
with
longer-term 12-mo (14) follow-up was not statistically
significant.
Measures of dietary sodium intake
A total of 7 studies measured dietary sodium intake. Five
studies were pooled (570 participants) (42, 50, 56, 57, 63),
TELEHEALTH DIET INTERVENTIONS IN CHRONIC
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showing that telehealth interventions reduced dietary sodium
intake on urinary and/or self-assessed scores [SMD: 20.39 (95%
CI: 20.58, 20.20), P = 0.0001, I2 = 19%] compared with
nontelehealth interventions (Figure 1). All 7 studies used the
telephone as the telehealth delivery method and were conducted
in participants with CVD. Two studies used nonvalidated
tools for determining daily sodium intake, measuring tea-
spoons of salt (1 teaspoon being w6 g NaCl or 2300 mg Na)
(50), and determining a salted food score (56). Exclusion of
these studies from the analysis resulted in 3 studies that re-
ported on millimoles per liter of urinary sodium per day (42,
57, 63), which did not reach significance [MD: 28.27 mmol
(95% CI: 217.34, 0.79 mmol/L), P = 0.07, I2 = 24%]. We
could not statistically pool 2 studies; these are reported in
Supplemental Table 2. The results remained significant in 2
trials with 12-mo (42, 63) follow-up [MD: 26.00 (95% CI:
210.41, 21.59), P = 0.008, I2 = 0%].
Energy intake
A total of 3 studies [2172 participants, all with long-term
durations (12 mo–4 y)] measured energy intake (59, 61, 63).
The
telehealth intervention did not significantly reduce energy

intake [MD: 210.48 kcal (95% CI: 267.20, 46.25 kcal), P =
0.72,
I2 = 15%] compared with usual care. All 3 studies used the tele-
phone as the telehealth delivery method and were conducted in
participants with diabetes mellitus.
Sources of dietary fat intake
A total of 8 studies reported on measures of dietary fat intake
(13, 44, 46, 54–56, 61, 63), including total fat per day (13, 61,
63),
FIGURE 1 Forest plot of the effect of telehealth dietary
intervention on diet quality and dietary sodium. The
effectiveness of telehealth is presented by
using random effects. The means and SDs of changes from
baseline are reported for trials. Effects of trials are presented as
weights (percentages) and std.
mean differences (95% CIs). IV, inverse variance; std.,
standardized.
FIGURE 2 Forest plot of the effect of telehealth dietary
intervention on servings of fruit and vegetable intake. The
means and SDs of changes from
weights (percentages) and mean differences (95% CIs). IV,
inverse variance.
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percentage of calories from total fat (55), saturated fat intake
per
day (13, 56, 63), percentage of calories from saturated fat (55),
and the Kristal Fat and Fiber Behavior Scale (44). Telehealth
interventions did not significantly reduce total dietary fat intake
[MD: 20.10 g (95% CI: 21.90, 1.70 g), P = 0.91, I2 = 76%] in 4
studies (2427 participants), but did significantly reduce
saturated
fat compared with nontelehealth comparators [MD: 20.93 g
(95% CI: 21.51, 20.32 g), P = 0.002, I2 = 0%] in 2 studies (572
participants). Three studies could not be pooled statistically and
are reported in Supplemental Table 2. Long-term trials (12 mo–
4 y)
were not statistically significant (55, 61, 63).
Telehealth dietary intervention and clinical outcomes
A total of 21 studies measured clinical outcomes that we were

able to pool into the meta-analysis.
BP
The telehealth intervention significantly reduced SBP by MD
22.64 mm Hg [(95% CI: 25.12, 20.16 mm Hg), P = 0.04,
I2= 83%] in 12 studies with a median duration of 6 mo
(4202 participants) (40, 41, 46, 48–51, 53, 55, 57, 59, 61)
(Figure 3).
A subgroup analysis by chronic disease condition showed that
the result for SBP was more pronounced in people with diabe-
tes mellitus (59, 61) [MD: 25.91 mm Hg (95% CI: 211.14,
20.68 mm Hg), P = 0.03, I2= 69%] than in people with CVD
(40, 41, 46, 48–51, 53, 57) [MD: 21.31 mm Hg (95% CI: 23.39,
0.77 mm Hg), P = 0.22, I2 = 60%]. Diastolic BP (DBP) was not
significantly reduced following telehealth interventions [MD:
21.60 mm Hg (95% CI: 23.42, 0.22 mm Hg), P = 0.1, I2= 87%]
in 10 studies (3512 participants) (46, 48–51, 53, 55, 57, 59, 61).
Subgroup analysis by chronic disease condition did not alter the
result for DBP (data not shown). Four long-term trials
(durations
12–24 mo) did not result in significant change in both SBP and
DBP (40, 55, 59, 61).
Weight, BMI, and waist circumference
Weight was significantly reduced by dietary telehealth in-
terventions [MD: 20.80 kg (95% CI: 21.61, 0.00 kg), P = 0.05,
I2= 79%] in 8 studies (974 participants) (14, 42, 44, 46, 53, 57,
59, 63) (Figure 3). Seven studies reported nonsignificant
changes in BMI (data not shown) in 3560 participants (14, 42,
50, 51, 54, 55, 60, 61, 63), and 5 studies reported a significant
FIGURE 3 Effects of telehealth dietary interventions on systolic
blood pressure (in milligrams of mercury), weight (in

kilograms), and waist circum-
ference (in centimeters). The means and SDs of changes from
weights (percentages) and mean
differences (95% CIs). IV, inverse variance.
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reduction in waist circumference in 1659 participants (49, 55,
59, 60,
63) of MD 22.08 cm (95% CI: 23.97, 20.20 cm; P = 0.03, I2 =

84%)
(Figure 3). BMI and weight were not changed significantly in
longer-term studies; however, waist circumference remained
significant in 4 trials with durations of 12–24 mo (55, 59, 60,
63)
[MD: 20.51 cm (95% CI: 20.73, 20.29 cm), P = 0.0001, I2 =
0%].
Serum lipids and glycated hemoglobin
Changes in serum lipids and glycated hemoglobin (HbA1c)
were reported in 11 studies. Telehealth interventions
significantly
reduced total cholesterol (44, 46, 49–51, 53, 55, 56, 59, 61, 63)
in
11 studies of 3697 participants [MD 20.08 mmol/L (95% CI:
20.16, 20.00 mmol/L), P = 0.04, I2 = 52%] (Figure 4). No
changes in LDL cholesterol (49–51, 53, 56, 59, 63), HDL cho-
lesterol (49, 51, 53, 56, 59, 63), or HbA1c (44, 59, 61) were ob-
served (data not shown). Triglycerides were significantly
reduced
following dietary telehealth interventions compared with usual
care
[MD 20.10 mmol/L (95% CI: 20.19, 20.01 mmol/L), P = 0.04,
I2 = 70%] in 7 studies encompassing 3268 participants (46, 49,
50,
56, 59, 61, 63) (Figure 4). Sensitivity analyses excluding
durations
of $2 y of follow-up (2 studies) of 2 (59) and 8 (61) y reduced
the
heterogeneity and resulted in an MD of 20.16 mmol/L [(95% CI:
20.26, 20.06 mmol/L), P = 0.001, I2 = 39%]. Long-term trials
(durations of 12 mo–4 y) did not result in significant changes in
biochemical outcomes (55, 59, 61, 63).
Mortality and hospitalizations

Two studies reported clinical endpoints and rates of hospi-
talizations (47, 52). Ferrante and colleagues (52) conducted
a 16-mo telephone intervention in patients with heart failure
(HF)
with contacts determined by severity of condition. The study
was
assessed as a low risk of bias and led to significantly reduced
all-
cause mortality in the telehealth group (15.3%) compared with
usual care (16.1%; P , 0.05), HF admission (16.8% and 22.3%,
respectively; P , 0.005), CV admission (24.1% and 30.1%,
respectively; P , 0.006), and all-cause admission (34.3% and
39.1%, respectively; P , 0.05). In the study by Albert et al.
(47), however, a 3-mo multifactorial lifestyle video and tele-
phone-based intervention in HF did not significantly reduce
rates of HF hospitalizations between groups and was a moderate
risk of bias study.
Risk of bias
Supplemental Figure 2 shows the risk of bias of the included
studies. The risk of bias was low-to-moderate across the in-
cluded studies. The majority (92%) of studies had adequate
randomization; however, concealed allocation was reported in
only 48% of the included studies, suggesting potential selection
bias. Double blinding was achieved in only 1 study (49), and
blinding of participants to treatment arm only was done in 1
study (41); however, intervention staff was aware of treatment
allocation. All other trials were not able to blind participants,
given the nature of dietary intervention to facilitate and modify
behavior change. This means that detection bias was high in
80% of the dietary measures because they were self-reported.
Attrition bias (through high loss to follow-up and no
explanation

of how such data were addressed) was judged to be high in 32%
of studies. Furthermore, there appears to be reporting bias in
FIGURE 4 Effects of telehealth dietary interventions on total
cholesterol and triglycerides (in millimoles per liter). The
means and SDs of changes from
weights (percentages) and mean differences (95% CIs). IV,
inverse variance.
1698 KELLY ET AL.
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$20% of the included studies because they did not report out-
comes that were stated in methods or protocol articles; 6 were
rectified on contact with corresponding authors. When the
Grading of Recommendations Assessment, Development
and Evaluation (directness, precision, consistency, and study
lim-
itations) recommendations were considered, the evidence
quality
for diet quality and fruit and vegetable intake was believed to
be
moderate, given that the dietary intake data were self-reported.
DISCUSSION
This systematic review assessed the effectiveness of complex
telehealth dietary interventions for facilitating dietary change in
adults with chronic disease. The primary finding was that
dietary
interventions delivered by telehealth effectively improved
dietary
adherence on a moderate scale and made small improvements in
diet quality (38). Single macronutrients were less likely to be
modified by telehealth intervention, including energy and …
Cochrane
Library
Cochrane Database of Systematic Reviews
Interventions to enhance adherence to dietary advice for
preventing
and managing chronic diseases in adults (Review)

Desroches S, Lapointe A, Ratté S, Gravel K, Légaré F,
Turcotte S
Desroches S, Lapointe A, Ratté S, Gravel K, Légaré F,
Turcotte S.
preventing and managing chronic diseases in adults.
Cochrane Database of Systematic Reviews 2013, Issue 2. Art.
No.: CD008722.
DOI: 10.1002/14651858.CD008722.pub2.
www.cochranelibrary.com
preventing and managing chronic diseases in adults
(Review)
Copyright © 2013 The Cochrane Collaboration. Published by
John Wiley & Sons, Ltd.
https://doi.org/10.1002%2F14651858.CD008722.pub2
https://www.cochranelibrary.com
Cochrane
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Trusted evidence.
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Better health.

T A B L E O F C O N T E N T S
HEADER................................................................................
...............................................................................................
.......................... 1
ABSTRACT............................................................................
...............................................................................................
.......................... 1
PLAIN LANGUAGE
SUMMARY.............................................................................
.......................................................................................... 2
BACKGROUND......................................................................
...............................................................................................
......................... 3
OBJECTIVES..........................................................................
...............................................................................................
......................... 4
METHODS..............................................................................
...............................................................................................
........................ 4
RESULTS...............................................................................
...............................................................................................
.......................... 7
Figure
1.............................................................................................
...............................................................................................
...... 8

Figure
2............................................................................................ .
...............................................................................................
...... 12
Figure
3.............................................................................................
...............................................................................................
...... 16
Figure
4.............................................................................................
...............................................................................................
...... 17
Figure
5.............................................................................................
...............................................................................................
...... 18
DISCUSSION..........................................................................
...............................................................................................
......................... 24
AUTHORS'
CONCLUSIONS................................................................... ...
...............................................................................................
...... 26
ACKNOWLEDGEMENTS........................................................
...............................................................................................
......................... 27
REFERENCES.........................................................................
...............................................................................................

........................ 28
CHARACTERISTICS OF
STUDIES................................................................................
.................................................................................. 43
DATA AND
ANALYSES............................................................................
...............................................................................................
......... 109
Analysis 1.1. Comparison 1 Nutritional tools versus control in
diet adherence, Outcome 1 Continuous
data................................ 110
Analysis 2.1. Comparison 2 Multiple interventions versus
control in diet adherence, Outcome 1 Continuous
data...................... 113
Analysis 2.2. Comparison 2 Multiple interventions versus
control in diet adherence, Outcome 2 Dichotomous
data................... 114
ADDITIONAL
TABLES.................................................................................
...............................................................................................
.... 115
APPENDICES.........................................................................
...............................................................................................
......................... 134
CONTRIBUTIONS OF
AUTHORS..............................................................................
..................................................................................... 137

DECLARATIONS OF
INTEREST..............................................................................
....................................................................................... 137
SOURCES OF
SUPPORT...............................................................................
.................................................................................... ...........
. 137
DIFFERENCES BETWEEN PROTOCOL AND
REVIEW.................................................................................
................................................... 138
INDEX
TERMS...................................................................................
...............................................................................................
............. 138
preventing and managing chronic diseases in adults (Review)
i
Cochrane
Library
Trusted evidence.
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[Intervention Review]
preventing and
managing chronic diseases in adults
Sophie Desroches1,2, Annie Lapointe1,2, Stéphane Ratté1,
Karine Gravel2, France Légaré3, Stéphane Turcotte1
1Centre de recherche du Centre hospitalier universitaire de
Québec (CHUQ), St-François d'Assise Hôpital, Québec, Canada.
2Département des sciences des aliments et de nutrition,
Université Laval, Québec, Canada. 3Département de médecine
familiale et
d'urgence, Université Laval, Québec, Canada
Contact address: Sophie Desroches, Centre de recherche du
Centre hospitalier universitaire de Québec (CHUQ), St-François
d'Assise
Hôpital, 10 Rue de l'Espinay, OGice D6-740, Québec, Québec,
G1L 3L5, Canada. [email protected]
Editorial group: Cochrane Consumers and Communication
Group
Publication status and date: New, published in Issue 2, 2013.
Citation: Desroches S, Lapointe A, Ratté S, Gravel K, Légaré F,
Turcotte S. Interventions to enhance adherence to dietary advice
for
preventing and managing chronic diseases in adults. Cochrane
Database of Systematic Reviews 2013, Issue 2. Art. No.:
CD008722. DOI:
10.1002/14651858.CD008722.pub2.

A B S T R A C T
Background
It has been recognized that poor adherence can be a serious risk
to the health and wellbeing of patients, and greater adherence to
dietary
advice is a critical component in preventing and managing
chronic diseases.
Objectives
To assess the eGects of interventions for enhancing adherence
to dietary advice for preventing and managing chronic diseases
in adults.
Search methods
We searched the following electronic databases up to 29
September 2010: The Cochrane Library (issue 9 2010), PubMed,
EMBASE
(Embase.com), CINAHL (Ebsco) and PsycINFO (PsycNET)
with no language restrictions. We also reviewed: a) recent years
of relevant
conferences, symposium and colloquium proceedings and
abstracts; b) web-based registries of clinical trials; and c) the
bibliographies of
included studies.
Selection criteria
We included randomized controlled trials that evaluated
interventions enhancing adherence to dietary advice for
preventing and

managing chronic diseases in adults. Studies were eligible if the
primary outcome was the client’s adherence to dietary advice.
We defined
'client' as an adult participating in a chronic disease prevention
or chronic disease management study involving dietary advice.
Data collection and analysis
Two review authors independently assessed the eligibility of the
studies. They also assessed the risk of bias and extracted data
using a
modified version of the Cochrane Consumers and
Communication Review Group data extraction template. Any
discrepancies in judgement
were resolved by discussion and consensus, or with a third
review author. Because the studies diGered widely with respect
to interventions,
measures of diet adherence, dietary advice, nature of the
chronic diseases and duration of interventions and follow-up,
we conducted a
qualitative analysis. We classified included studies according to
the function of the intervention and present results in a
narrative table
using vote counting for each category of intervention.
1
mailto:[email protected]
https://doi.org/10.1002%2F14651858.CD008722.pub2

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Main results
We included 38 studies involving 9445 participants. Among
studies that measured diet adherence outcomes between an
intervention
group and a control/usual care group, 32 out of 123 diet
adherence outcomes favoured the intervention group, 4 favoured
the control
group whereas 62 had no significant diGerence between groups
(assessment was impossible for 25 diet adherence outcomes
since data
and/or statistical analyses needed for comparison between
groups were not provided). Interventions shown to improve at
least one
diet adherence outcome are: telephone follow-up, video,
contract, feedback, nutritional tools and more complex
interventions including
multiple interventions. However, these interventions also shown
no diGerence in some diet adherence outcomes compared to a
control/
usual care group making inconclusive results about the most
eGective intervention to enhance dietary advice. The majority
of studies
reporting a diet adherence outcome favouring the intervention
group compared to the control/usual care group in the short-

term also
reported no significant eGect at later time points. Studies
investigating interventions such as a group session, individual
session, reminders,
restriction and behaviour change techniques reported no diet
adherence outcome showing a statistically significant diGerence
favouring
the intervention group. Finally, studies were generally of short
duration and low quality, and adherence measures varied
widely.
Authors' conclusions
There is a need for further, long-term, good-quality studies
using more standardized and validated measures of adherence to
identify the
interventions that should be used in practice to enhance
adherence to dietary advice in the context of a variety of
chronic diseases.
P L A I N L A N G U A G E S U M M A R Y
preventing and managing chronic diseases in adults
Chronic diseases are the leading cause of mortality worldwide.
Although the adoption of a healthy diet is recognized as an
important
component for their prevention and management, many
individuals at risk of or having chronic diseases do not adhere
to recommended
dietary advice. The methods used to facilitate changes in dietary
habits through dietary advice (defined in this review as
'interventions')
could improve adherence of clients to dietary advice. Therefore,
we reviewed trials of interventions aiming to enhance adherence

to dietary
advice for preventing and managing chronic diseases in adults.
We identified 38 studies involving 9445 participants examining
several types of interventions for enhancing adherence to
dietary advice
for preventing and managing many chronic diseases. The main
chronic diseases involved were cardiovascular diseases,
diabetes,
hypertension, and renal diseases. Interventions shown to
improve at least one diet adherence outcome are: telephone
follow-up, video,
contract, feedback, nutritional tools and more complex
interventions including multiple interventions. However, these
interventions also
showed no diGerence in some diet adherence outcomes
compared to a control/usual care group making the results
inconclusive about
the most eGective intervention to enhance dietary advice.
Interestingly, all studies including clients with renal diseases
reported at least
one diet adherence outcome showing a statistically significant
diGerence favouring the intervention group, no matter which
intervention
was provided. The majority of studies reporting a diet
adherence outcome favouring the intervention group compared
to the control/
usual care group in the short-term also reported no significant
eGect at later time points. Studies investigating interventions
such as a
group session, individual session, reminders, restriction and
behaviour change techniques reported no diet adherence
outcome showing
a statistically significant diGerence favouring the intervention
group. Finally, interventions were generally of short duration,
studies used

diGerent methods for measuring adherence and the quality of
the studies was generally low.
2
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B A C K G R O U N D
Description of the condition
Chronic diseases are defined as diseases of long duration that
have generally a slow progression (WHO 2008). The most
common
chronic diseases include diabetes, cardiovascular diseases
(CVD),
cancers, asthma, chronic obstructive pulmonary diseases
(COPD),
arthritis, obesity and renal failure. Considering that chronic
diseases are the leading cause of death and disability and

account
for 60% of all deaths worldwide (WHO 2008), the Department
of Chronic Disease and Health Promotion of the World Health
Organization (WHO) emphasizes the importance of preventing
and
managing chronic diseases and their risk factors (WHO 2010).
Some
health conditions have been found to be risk factors, for
example,
patients with the metabolic syndrome have an increased risk of
developing CVD (Mottillo 2010). Similarly, women with a
previous
history of gestational diabetes have an increased risk of
developing
type II diabetes (Bellamy 2009). These risk factors may be
targeted
in interventions aiming to prevent chronic diseases.
Evidence from epidemiologic, experimental and clinical studies
has demonstrated a strong relationship between dietary patterns
or nutrient intakes, and prevention and management of chronic
diseases including diabetes (Champagne 2009), CVD (Lavie
2009),
and obesity (Kennedy 2004). Several authoritative health
agencies
have recommended the adoption of a healthy diet as the
cornerstone in preventing and/or managing chronic diseases
such
as CVD (Lichtenstein 2006), diabetes (Bantle 2008) and cancer
(Kushi 2006). For example, lifestyle interventions including
dietary
changes were shown to reduce the incidence of diabetes by 58%
compared to a control group in individuals at high risk in two
large randomized controlled trials (RCTs): the Finnish Diabetes
Prevention study (Lindstrom 2003) and the Diabetes Prevention
Program (Knowler 2002). In line with this, dietitians and other

health professionals provide people with dietary advice
designed
to improve their nutritional intake (Baldwin 2011).
The concept of 'adherence' recognizes the patient’s right to
choose
whether or not to follow advice, and implies a patient’s active
participation in the treatment regimen (Cohen 2009). For
chronic
disease management including medication and lifestyle changes,
non-adherence rates are estimated to be between 50% and 80%
(WHO 2003). Thus, poor adherence can be a serious threat to
patients’ health and wellbeing (DiMatteo 2002), and also carries
an economic burden (DiMatteo 2004a). Adherence is
particularly
important in the context of chronic diseases requiring long-term
therapy and a number of permanent rather than temporary
changes in lifestyle behaviours, such as diet, physical activity
and smoking (WHO 2003). The extent to which risk-reduction
interventions proved to be as eGective in research settings as in
individuals' real-life settings depends on the patient’s adherence
to treatment advice. In that regard, results from an RCT
assessing
adherence to and eGectiveness of four popular diets (Atkins,
Zone,
Weight Watchers, and Ornish) revealed that level of adherence
to dietary advice, rather than the type of diet, was the key
determinant of greater weight loss and CVD risk factor
reductions
(Dansinger 2005). Whether the number of intervention goals
that
an individual has to reach influences adherence was also
addressed
in a secondary analysis of the PREMIER study (Young 2009).
In
this RCT that tested the eGects of two multicomponent lifestyle

interventions on blood pressure control, the authors reported
that
individuals with the most physical activity and dietary
behaviour
goals to achieve reached the most goals (Young 2009).
Measurement of adherence to prescribed dietary advice
typically
involves: 1) assessment of what the client eats through self-
reported methods (e.g. 24-hour recall, food records, food
frequency
questionnaires, diet history); and 2) determination of the degree
to
which the diet approximates the recommended dietary plan (e.g.
diGerence between clients’ recommended macronutrient goals
and their self-reported intake). Although sparsely used, more
objective measures of adherence to diets also exist (e.g. 24-hour
urinary sodium excretion to assess adherence to a low sodium
diet
(Chung 2008)). However, there is no gold standard for the
accurate
determination of dietary intake. Self-report of energy intake is a
characteristic inherent to nutrition-related topics and is found to
be underestimated compared to objective measures such as
resting
energy expenditure assessed by indirect calorimetry (Asbeck
2002).
Underreporting energy intake has been observed more
frequently
in women versus men, (Johnson 1994), in older versus young
(Huang 2005), and in obese versus normal weight individuals
(Briefel 1997). Although self-report measures are oSen regarded
as susceptible to bias (e.g. over reliance on memory; report
error related to meal composition or portion sizes; daily dietary
variability; social desirability) (Kumanyika 2000; Wilson 2005)

they
are a direct, simple and inexpensive method (DiMatteo 2004b),
and
are readily available for use in practice. Self-report measures
can be
improved and validated by using multiple measures of
adherence
and controlling statistically for bias or by using constructs such
as
body weight, blood pressure or plasma cholesterol
concentrations
(Hebert 2001; DiMatteo 2004b).
Description of the intervention
Adherence to dietary advice has been shown to vary according
to gender (Chung 2006), socio-economic status (Reid 1984) and
ethnicity (Natarajan 2009). Moreover, numerous barriers to
client
adherence in health care have been identified. Among them are
complexity of treatment plan, and clients’ knowledge of disease
and understanding of the importance of treatment in its control
and
in preventing adverse outcomes (Makaryus 2005 ;Harmon 2006;
Robinson 2008). According to a WHO report, "interventions for
removing barriers to adherence must become a central
component
of eGorts to improve population health worldwide" (WHO
2003).
Although non-adherence is oSen attributed to clients who are
viewed as "non cooperative", "non compliant" and "unable to
follow instructions" (Kapur 2008), it is increasingly recognized
that
health professionals may help their clients overcome barriers to
adherence (Harmon 2006) by improving how they approach
their

clients' problems, how they provide advice, and how they
involve
their clients in treatment decision making. Although there is a
wide diversity of interventions for enhancing adherence to
dietary
advice, their underlying aim is to prompt change to facilitate the
adoption of recommended dietary behaviours.
How the intervention might work
Behaviour change theories have proved useful for explaining
health-related behaviours, including dietary behaviours. They
attempt to identify the determinants that will contribute to
predict
the adoption of a specific behaviour, and which should be taken
into account when developing a behaviour change intervention,
such as a method for providing dietary advice. Several models
or theories to predict behaviour change can be used in health-
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related interventions, such as the Health Belief Model
(Rosenstock
1974), the Theory of Planned Behaviour (Ajzen 1991), the
Theory
of Reasoned Action (Fishbein 1981) and the Social Cognitive
Theory (Bandura 1986). More recently, Michie 2011 proposed
a framework, the COM-B system, which includes three principal
interrelated components of the determination of a behaviour: 1)
the motivation (the direct brain process leading to a behaviour),
2) the capability (the individual’s psychological and physical
capacity to engage a behaviour) and 3) the opportunity (the
factors that lie outside the individual that make the behaviour
possible or not) (Michie 2011).The authors also developed a
system for characterizing behaviour change interventions and
their components in order to facilitate the identification of the
eGective behaviour change interventions and the
implementation
of evidence-based practice in this area. According to this
system, behaviour change interventions can be classified as nine
intervention functions: education, persuasion, incentivisation,
coercion, training, restriction, environmental restructuring,
modelling and enablement (Michie 2011). These theories or
models
focus on diGerent determinants or combinations of determinants
of
the behaviours which could be helpful for developing
interventions
for enhancing adherence to dietary advice.
Why it is important to do this review
As greater adherence to dietary advice is a critical component in
preventing and managing chronic diseases, research is needed to

identify the characteristics of interventions that will result in a
better agreement between health professionals’ evidence-based
dietary advice, and their clients’ eating patterns. Despite
growing
recognition that non-adherence to dietary advice is a barrier to
getting new nutrition knowledge into practice, previous
knowledge
syntheses have provided decision makers and knowledge users
with little practical guidance on the development of useable
interventions for enhancing adherence to dietary advice. Studies
have reported on interventions designed to enhance adherence to
dietary advice by overcoming barriers to adherence. Although
some
studies have reported positive eGects of interventions to
enhance
adherence to dietary advice, no systematic review specifically
assesses dietary interventions that lead to sustained dietary
changes or that refer to a wide array of chronic diseases.
Haynes
2008 summarized the results of RCTs of interventions to help
clients
adhere to prescriptions for medications for medical problems,
and
excluded interventions targeting dietary advice. Bosch-
Capblanch
2007 systematically reviewed the eGects of contracts between
clients and health professionals for improving clients' adherence
to treatment, prevention and health promotion activities.
Although
this review is relevant to our review, it reported only the eGect
of
contracts (as opposed to other interventions), and was not
specific
to dietary advice. Several non-Cochrane reviews may overlap
with
our review, but these are not systematic (Brownell 1995b;

Brownell
1995a; Burke 1997; Newell 2000; Fappa 2008) and/or are
related
to only one health condition and not specifically targeting
dietary
advice (Burke 1997; Newell 2000; Fappa 2008).
This review will improve the knowledge base for adherence to
dietary advice; a topic of immense importance for dietetics
practice
that will also be relevant to clients, and other health
professionals.
O B J E C T I V E S
To assess the eGects of interventions for enhancing adherence
to
dietary advice for preventing and managing chronic diseases in
adults.
M E T H O D S
Criteria for considering studies for this review
Types of studies
Randomized controlled trials (RCTs) including cluster RCTs.
Because interventions for enhancing adherence to dietary advice
aim to initiate dietary changes, a cross-over design in which
each
client received all interventions could induce a carry-over
eGect.
Therefore, we excluded studies including a cross-over design.
Types of participants

Clients, aged 18 years and over, in real-life settings. We define
'client' as an adult participating in a chronic disease prevention
or chronic disease management study involving dietary advice.
We included clients who had a diet related-chronic disease (e.g.
obesity, cardiovascular disease, renal failure, hypertension) or
at least one risk factor for a chronic disease (e.g. overweight,
hyperlipidaemia). We included family or non-family caregivers
such
as wife/husband or individual living with the client and
involved in
meal planning and preparation. We also included studies
involving
health professionals delivering dietary advice.
Types of interventions
We included studies assessing the eGects of a single
intervention
or multiple interventions involving chronic disease prevention
and
management, on adherence to dietary advice. 'Intervention' was
defined as the method used to facilitate changes in dietary
habits
through dietary advice. To structure the presentation of results,
we
grouped interventions according to the intervention functions of
the behaviour change wheel developed by Michie and
colleagues
(Michie 2011). Therefore, we classified interventions to
enhance
adherence to dietary advice as:
• Education (increasing knowledge or understanding);
• Persuasion (using communication to induce positive or
negative

feelings or stimulate action);
• Incentivisation (creating expectation of reward);
• Coercion (creating expectation of punishment or cost);
• Training (imparting skills);
• Restriction (using rules to reduce the opportunity to engage in
the target behaviour);
• Environmental restructuring (changing the physical or social
context);
• Modelling (providing an example for people to aspire to or
imitate) ;
• Enablement (increasing means/reducing barriers to increase
capability or opportunity);
• Multiple (combination of two or more diGerent interventions).
We included studies making the following comparisons:
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• Single intervention for enhancing adherence to dietary advice
versus no intervention (control) or a reference standard of care
(usual care);
• Single intervention for enhancing adherence to dietary advice
versus single or multiple interventions with a similar purpose
(to
enhance adherence to dietary advice);
• Multiple interventions for enhancing adherence to dietary
advice versus no intervention (control) or a …
Topic
Interventions to improve nutritional status
Question
What type of interventions improve adherence to
recommendations on nutritional intake?
Read the study article and the additional research article to
answer the above question, according to the topic chosen, in a 3
full page (not including title and reference page) summary (use
the two articles to answer the question to support your
statement).
The Summary must include the following headings
1. Introduction and Key Points
Defines the Topic and Question
Importance of the topic
Why did you pick the topic and why should we as nurses’ care
about this topic?

States why it is a problem
2. Article Search (only for additional article)
Current and credible resource
Database search-terms and methods (key terms used; how you
found the article)
Number of articles located (how you narrowed the search, how
you ultimately selected the article that you selected).
3. Article Findings (for the two articles)
How it addresses the topic
Type of Research conducted (quantitative or qualitative)
Findings of research (who was studied, how they were studied,
who the population was, what tools were used for the study,
what were the important findings / results)
4. Evidence for Practice
Summary of evidence
How it will improve nursing practice of the bedside
How will this evidence decrease a gap in practice?
Any concerns or weaknesses located in the evidence
5. Sharing of Evidence
Who would you share the information with?
How would you share this information (e.g through PowerPoint,
brochures, community meetings, etc)?
What resources would you need to accomplish this sharing of
evidence (e.g a community space for a community meeting, a
projector for a PowerPoint presentation, etc)?
Why would it be important to share this evidence with the
nursing profession?
6. Conclusion
Summarizes the theme of the paper.
Information presented in logical sequence.
All key points addressed
Note: Conclusion shows depth of understanding.
Writing Requirements
3 full pages (not less, not more please).
APA style used properly for in- text citations, references, and
quotation.

All references are cited, and all citations have references (the
references are the two articles used)

Telehealth dietary interventions improve diet quality in chronic disease

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