Keywords
celiac disease - gluten-free diet - adherence - pediatric - systematic review
Introduction
The prevalence of celiac disease (CD) in Europe is approximately 1%.[1] The pathophysiology for CD involves a multisystemic autoimmune-mediated disorder
to gluten, a protein most commonly found in wheat, rye, and barley resulting in injury
to the small bowel mucosa.[2] Genetic susceptibility with HLA DQ-2 and/or DQ-8 positivity is strongly associated
with the disease.[2]
Diagnosing CD is challenging due to its nonspecific and heterogeneous clinical presentation.
The symptoms can vary in intensity but commonly it presents with abdominal symptoms
such as malabsorption, discomfort, loose stools, and flatulence[3] and a variety of nonintestinal symptoms that include short stature, infertility,
delayed puberty, anemia, liver abnormalities, joint and muscular disorders, neurological
complications, psychiatric disorders and cutaneous and mucosal manifestations.[4] Importantly, CD can also affect asymptomatic patients.[3]
Regarding the treatment of CD, the only knowledgeable efficient treatment is a gluten-free
diet (GFD).[3] Without the exposure to gluten, the symptoms as well as the damage inflicted, regress
and the patient becomes asymptomatic.[2] Nevertheless, it represents a major lifelong change in lifestyle. Compliance with
GFD can be challenging, onerous, expensive, and imposes difficulties to the patient.[5] Hence, the need for a systematic review to identify factors that interfere with
GFD compliance and to recognize predictors of noncompliance as well as modifiable
factors that positively influence compliance is fully justified.
Methods
Search Strategy
We searched the PubMed database for literature regarding the compliance to GFD in
pediatric CD from inception to April 16, 2019. The terms used to perform the search
were as follows: celiac or celiac or gluten sensitive enteropathy AND diet$ or nutrition$
or GFD or gluten-free or gluten free AND advice or adherence or compliance or concordance
or prescription or intervention or management AND child$ or pediatric$. No filter
was applied.
Eligibility Criteria for Studies and Participants
The inclusion criteria were a study population that included parents of or children
under 18 years old throughout the entire study course; confirmed diagnostic of CD
without related comorbidities; and focus on the factors influencing compliance to
a GFD.
The exclusion criteria were articles not written in English and gray literature.
Study Selection and Data Extraction
Study selection was performed independently by two authors (V.M.-C. and R.M.-C.).
Discrepancies were resolved through discussion among them or by consulting a third
author (H.A.). A PRISMA flowchart ([Fig. 1]) was used to perform this record.
Fig. 1 Flowchart representing the study selection process.
Prior to data extraction, the authors through the analysis of the papers herein included
develop an excel form to systematically extract data (V.M.-C. and R.M.-C.). The form
contemplated the following detailed parameters: title, authors, country of origin,
year of publication, study design, participant number, mean participant age, the specific
aim of study, methods used to assess compliance, and factors related with GFD compliance.
Study Quality and Assessment of Risk Bias
Quality was individually assessed by two authors (V.M.-C. and R.M.-C.). The authors
resolved any disagreement through discussion of each dissonant parameter. When agreement
could not be reached, a third author was consulted (H.A.).
Since the articles retrieved were cohort, cross-sectional, and case–control studies,
the authors decided to assess quality using the National Heart, Lung and Blood Institute
Study Quality Assessment Tools.[6] This checklist comprises 12 questions for case–control studies and 14 questions
for cross-sectional and cohort studies. The questions must be answered using “Yes,”
“No,” or “Cannot be applied/Not answered/Not reported.”
After finalizing the quality assessment, the articles were divided into three groups
rated as “Good,” “Medium,” or “Poor” according to their final scores. To obtain these
subcategories, we excluded the questions in which all the articles scored the same.
This information is summarized in [Tables 1] and [2].
Table 1
Quality assessment of case–control studies
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
|
|
Chauhan et al
|
+
|
+
|
−
|
−
|
+
|
+
|
?
|
−
|
+
|
+
|
+
|
?
|
Good
|
|
Wagner et al
|
+
|
+
|
−
|
−
|
+
|
+
|
?
|
−
|
+
|
+
|
+
|
−
|
Medium
|
|
Ljungman and Myrdal et al
|
+
|
−
|
−
|
+
|
−
|
+
|
?
|
−
|
+
|
−
|
+
|
−
|
Poor
|
([−], “No”; [?], “Cannot Determine/Not Applicable/Not Reported”; [+], “Yes”) (1. Was
the research question or objective in this paper clearly stated and appropriate?;
2. Was the study population clearly specified and defined?; 3. Did the authors include
a sample size justification?; 4. Were controls selected or recruited from the same
or similar population that gave rise to the cases (including the same timeframe)?;
5. Were the definitions, inclusion and exclusion criteria, algorithms or processes
used to identify or select cases and controls valid, reliable, and implemented consistently
across all study participants?; 6. Were the cases clearly defined and differentiated
from controls?; 7. If less than 100% of eligible cases and/or controls were selected
for the study, were the cases and/or controls randomly selected from those eligible?;
8. Was there use of concurrent controls?; 9. Were the investigators able to confirm
that the exposure/risk occurred prior to the development of the condition or event
that defined a participant as a case?; 10. Were the measures of exposure/risk clearly
defined, valid, reliable, and implemented consistently (including the same time period)
across all study participants?; 11. Were the assessors of exposure/risk blinded to
the case or control status of participants?; 12. Were key potential confounding variables
measured and adjusted statistically in the analyses? If matching was used, did the
investigators account for matching during study analysis?)
Table 2
Quality assessment of cross-sectional studies
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
|
|
Mager et al
|
+
|
+
|
+
|
+
|
−
|
−
|
−
|
+
|
+
|
−
|
+
|
?
|
?
|
+
|
Good
|
|
Anson et al
|
+
|
+
|
+
|
+
|
−
|
−
|
−
|
+
|
−
|
−
|
+
|
+
|
?
|
−
|
Medium
|
|
Sarkhy et al
|
+
|
+
|
?
|
+
|
+
|
−
|
−
|
+
|
+
|
−
|
+
|
+
|
?
|
+
|
Good
|
|
Charalampopoulos et al
|
+
|
+
|
+
|
+
|
−
|
−
|
−
|
−
|
+
|
−
|
+
|
+
|
?
|
+
|
Medium
|
|
Taghdir et al
|
+
|
+
|
+
|
+
|
−
|
−
|
−
|
+
|
+
|
−
|
+
|
?
|
?
|
−
|
Medium
|
|
Khurana et al
|
+
|
−
|
?
|
+
|
−
|
−
|
−
|
+
|
+
|
+
|
+
|
?
|
?
|
−
|
Poor
|
|
MacCulloch and Rashid
|
+
|
+
|
+
|
+
|
+
|
−
|
−
|
+
|
+
|
−
|
+
|
+
|
?
|
−
|
Good
|
|
Garg and Gupta
|
+
|
+
|
?
|
+
|
−
|
−
|
−
|
+
|
+
|
−
|
+
|
+
|
?
|
+
|
Good
|
|
Roma et al
|
+
|
+
|
?
|
+
|
−
|
−
|
−
|
−
|
−
|
−
|
+
|
+
|
?
|
−
|
Poor
|
([−], “No”; [?], “Cannot determine/not applicable/not reported”; [+], “Yes”) (1. Was
the research question or objective in this paper clearly stated?; 2. Was the study
population clearly specified and defined?; 3. Was the participation rate of eligible
persons at least 50%?; 4. Were all the subjects selected or recruited from the same
or similar populations (including the same time period)? Were inclusion and exclusion
criteria for being in the study prespecified and applied uniformly to all participants?;
5. Was a sample size justification, power description, or variance and effect estimates
provided?; 6. For the analyses in this paper, were the exposure(s) of interest measured
prior to the outcome(s) being measured?; 7. Was the timeframe sufficient so that one
could reasonably expect to see an association between exposure and outcome if it existed?;
8. For exposures that can vary in amount or level, did the study examine different
levels of the exposure as related to the outcome (e.g., categories of exposure, or
exposure measured as continuous variable)?; 9. Were the exposure measures (independent
variables) clearly defined, valid, reliable, and implemented consistently across all
study participants?; 10. Was the exposure(s) assessed more than once over time?; 11.
Were the outcome measures (dependent variables) clearly defined, valid, reliable,
and implemented consistently across all study participants?; 12. Were the outcome
assessors blinded to the exposure status of participants?; 13. Was loss to follow-up
after baseline 20% or less?; 14. Were key potential confounding variables measured
and adjusted statistically for their impact on the relationship between exposure(s)
and outcome(s)?).
Results
Description of Study Selection
The flowchart in [Fig. 1] shows a schematic presentation of the selection process of studies included.[7] After searching PubMed using the keywords as described earlier, we obtained a total
of 1,414 results. Nevertheless, 1,379 papers were excluded based on their title or/and
abstract. Exclusion was based on the article type (systematic review, meta-analyses,
comment, expert opinion, or letter), CD being associated with some comorbidity, compliance
to GFD not being the main aim, and population over 18 years old. Of the 35 articles
that remained for full text assessment, 23 articles were not eligible based on the
following premises: seven studied population with patients older than 18 years old,
five did not regard CD, four did not correlate with compliance, four presented no
comparable data, two with no statistical evidence and one could not be accessed in
time for this review. A total of 12 articles were finally analyzed.
Methodological Quality
Of the included studies, nine are cross-sectional (75%) and three are case–control
(25%) studies. Two cross-sectional studies and one case–control article were rated
as “Poor.” This rating was tied to the following assessments: Khurana et al[8] lacked information regarding population details and Roma et al[9] and Ljungman and Myrdal[10] did not discriminate the factors affecting compliance, namely those that were evaluated
as a dichotomic variable when more discrimination was possible.
The cross-sectional papers that scored the lowest were because of the following reasons:
justifying and pretending the results of statistical analysis, exposure being measured
before assessing the outcome, the time frame used, number of exposure assessment,
number of participants lost to follow-up (not applicable to this type of study), and
identification of potential confounding factors.
Regarding case–control studies, the items where all papers scored the lowest were
the justification for the sample size and the use of concurrent controls.
Characterization of the Population
Data concerning the population at study is summarized in [Table 3]. A population of 1,579 children was included in our study. None of the papers used
populations smaller than 40 patients? Four articles[10]
[11]
[12]
[13] did not display the mean age and two described it using a median statistic.[14]
[15] Therefore, we were able to estimate an average CD patient age of 10.3 years. The
papers report to different geographic areas with five being from Europe,[9]
[10]
[12]
[14] three from India,[8]
[11]
[13] another three from Middle East,[5]
[16]
[17] and two from Canada.[15]
[18] Except for two of them,[10]
[17] all papers were published within the last decade. [Table 3] also elucidates on the method and criteria used for the diagnosis of CD.
Table 3
Characterization of the population at study and criteria for the diagnosis of CD
|
Authors
|
Country
|
Year
|
Study design
|
Study population
|
Age mean ± SD
|
Criteria used for the diagnosis of CD
|
Biopsy to confirm CD
|
|
Mager et al
|
Canada
|
2018
|
Cross sectional
|
372
|
10.4 ± 3.8 (CD)10.9 ± 4.0 (controls)
|
Nondisclosed
|
Performed
|
|
Chauhan et al
|
India
|
2010
|
Case–control
|
70
|
−
|
ESPGHAN 2012
|
Performed
|
|
Anson et al
|
Israel
|
1989
|
Cross sectional
|
43
|
10.7
|
Nondisclosed
|
Performed
|
|
Sarkhy et al
|
Saudi Arabia
|
2015
|
Cross sectional
|
133
|
9.9
|
Nondisclosed
|
Performed in 94% of population
|
|
Wagner et al
|
Austria
|
2016
|
Case–control
|
376
|
−
|
Nondisclosed
|
Performed
|
|
Ljungman and Myrdal
|
Sweden
|
1993
|
Case–control
|
47
|
−
|
ESPGHAN 1969
|
Performed
|
|
Taghdir et al
|
Iran
|
2016
|
Cross sectional
|
65
|
11.3 ± 3.8
|
ESPGHAN criteria (year nondisclosed)
|
Performed
|
|
Charalampopoulos et al
|
Greece
|
2013
|
Cross sectional
|
90
|
12.1 (median)
|
ESPGHAN 2012
|
Performed
|
|
Roma et al
|
Greece
|
2010
|
Cross sectional
|
73
|
10.4
|
ESPGHAN 1990
|
Performed
|
|
Khurana et al
|
India
|
2014
|
Cross sectional
|
50
|
9.06
|
ESPGHAN 1990
|
Performed
|
|
MacCulloch and Rashid
|
Canada
|
2014
|
Cross Sectional
|
126
|
12 (median)
|
Nondisclosed
|
Performed
|
|
Garg and Gupta
|
India
|
2014
|
Cohort
|
134
|
−
|
ESPGHAN 1990
|
Performed
|
Abbreviations: −, value was not disclosed; CD, celiac disease; ESPGHAN, European Society
for Paediatric Gastroenterology Hepatology and Nutrition.
Characterization of the Study
The analyses of [Tables 4] and [5] summarize the results of each paper considering the following categories: demographic
factor, household, child related, parent related, dietary related, disease related,
personality related, and quality of life (QoL).
Table 4
Discrimination of variables regarding demographic, household, child, and parent-related
factors
|
Demographic factors
|
|
Gender
|
Maternal age
|
Paternal age
|
Maternal education
|
Paternal education
|
Age
|
Non Caucasian
|
Born in Canada
|
Family history
|
Residence
|
Parental occupational status
|
Family type
|
Higher income per capita
|
Less number of siblings (0–1)
|
Parents' country of origin
|
Parents' marital status
|
Parents' labor force participation
|
Working or nonworking mother
|
|
Mager et al
|
x
|
x
|
x
|
x
|
x
|
|
♦
|
♦
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Chauhan et al
|
x
|
−
|
−
|
◊
|
−
|
♦
|
−
|
−
|
−
|
−
|
−
|
♦
|
♦
|
♦
|
−
|
−
|
−
|
−
|
|
Anson et al
|
x
|
−
|
−
|
♦
|
♦
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
x
|
x
|
−
|
|
Sarkhy et al
|
−
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
x
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Ljungman and Myrdal
|
♦
|
−
|
−
|
−
|
−
|
♦
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Taghdir et al
|
x
|
−
|
−
|
♦
|
♦
|
−
|
−
|
−
|
x
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Wagner et al
|
x
|
−
|
−
|
−
|
−
|
♦
|
−
|
−
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Charalampopoulos et al
|
−
|
−
|
−
|
−
|
−
|
♦[1]
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Roma et al
|
−
|
−
|
−
|
x
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Khurana et al
|
x
|
−
|
−
|
x
|
x
|
x
|
−
|
−
|
−
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
−
|
x
|
|
MacCulloch and Rashid
|
x
|
−
|
−
|
−
|
−
|
◊
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Garg and Gupta
|
x
|
−
|
−
|
♦0
|
x
|
♦[1]
|
−
|
−
|
−
|
−
|
−
|
♦[1]
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Demographic factors
|
Household
|
Child Related
|
|
Mother outside home
|
Siblings without CD
|
Province of living
|
Family income per capita
|
Occupational status of the father (Professional)
|
Social support or the lack of it
|
Habitation
|
Number of individuals in the household consuming a GFD
|
Number of children in the household
|
Household income were noted
|
Weight
|
Height
|
Site of investigation
|
Birth order
|
Number of siblings
|
Child knowledge of CD
|
Current BMI
|
|
Mager et al
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
x
|
x
|
x
|
x
|
x
|
x
|
−
|
−
|
−
|
−
|
|
Chauhan et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Anson et al
|
−
|
−
|
−
|
−
|
♦
|
x
|
−
|
−
|
|
−
|
−
|
−
|
−
|
x
|
x
|
−
|
−
|
|
Sarkhy et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Ljungman and Myrdal
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
x
|
−
|
−
|
−
|
♦
|
−
|
|
Taghdir et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
−
|
−
|
|
Wagner et al
|
−
|
−
|
−
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
♦
|
|
Charalampopoulos et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Roma et al
|
x
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
♦
|
−
|
|
Khurana et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
♦
|
♦
|
−
|
x
|
x
|
−
|
−
|
|
MacCulloch and Rashid
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Garg and Gupta
|
−
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
−
|
−
|
|
Parent Related
|
Parent Related
|
|
Parents easily discuss child’s condition
|
Parents felt child similar to other children
|
Parents easily interact with other parents
|
Parental knowledge of CD
|
Tendency to seek medical help
|
Concern about health of the child with CD
|
Parents consider child’s diet to be a burden
|
Parents consider child’s diet to strain family budget
|
Parents worry less about health
|
Concerned about future army service
|
Combined severity concerned
|
Evaluated parental knowledge of CD
|
Psychological burden on parents
|
Do not interact with parents of other CD children
|
Perception of the diet as a family burden
|
|
Mager et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Chauhan et al
|
x
|
x
|
x
|
♦
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
|
Anson et al
|
−
|
−
|
−
|
x
|
x
|
x
|
x
|
x
|
♦
|
♦
|
♦
|
−
|
−
|
−
|
−
|
|
Sarkhy et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
--
|
−
|
|
Ljungman and Myrdal
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Taghdir et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Wagner et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Charalampopoulos et al
|
−
|
−
|
−
|
♦[1]
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
−
|
−
|
−
|
|
Roma et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Khurana et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
MacCulloch and Rashid
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Garg and Gupta
|
♦0
|
−
|
−
|
♦0
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
♦0
|
♦0
|
−
|
Abbreviations: -, not studied; x, not found to be associated with compliance; ♦, found
to be associated with compliance; ◊, associated with noncompliance; 1, established
as a predictor after a logistic regression; 0, not established as a predictor after
logistic regression; CD, celiac disease; GFD, gluten free diet; GI, gastro intestinal
symptoms, ATTG.
Table 5
Discrimination of variables regarding dietary, disease, personality, and quality of
life-related factors
|
Dietary related
|
Dietary related
|
|
Ability to choose GFD food
|
Ability to choose GFD beverages in menu
|
Reports child demands food not GFD once a week
|
Difficulty maintaining GFD in parties and special occasions
|
Shared responsibility in mainting GFD
|
Availability of GFD
|
Hospital supply of GFD
|
Pricing of GFD
|
Budget spending on GFD
|
Perceived facility in maintaining diet
|
Difficulty to maintaining GFD at school
|
Difficulty to maintaining GFD at parties/ marriages
|
Likes gluten taste
|
No mistake in handling menu
|
Child perception of difficulty in maintaining GFD on travel
|
Child shares responsibility about disease
|
|
Mager et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Chauhan et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
♦
|
♦
|
♦
|
♦
|
−
|
−
|
−
|
|
Anson et al
|
♦
|
♦
|
♦
|
♦
|
♦
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Sarkhy et al
|
−
|
−
|
−
|
−
|
−
|
x
|
x
|
x
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Ljungman and Myrdal
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Taghdir et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Wagner et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Charalampopoulos et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
−
|
−
|
|
Roma et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Khurana et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
MacCulloch and Rashid
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Garg and Gupta
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
♦0
|
♦[1]
|
♦[1]
|
♦[1]
|
♦[1]
|
−
|
x
|
♦[1]
|
|
Disease Related
|
Disease Related
|
|
Child perception of difficulty in maintaining GFD with friends
|
Dinning in restaurants
|
Barriers to compliance: availability, cost, smaller communities
|
Age at diagnosis
|
Time since diagnosis
|
Comorbidities
|
Mean duration of CD
|
Serum ATTG levels
|
Gluten intake
|
No positive history of CD
|
Self-reported GI symptoms
|
Frequency of CD dx in the family
|
Delay at diagnosis
|
Symptomatic patient
|
Type of manifestation
|
Celiac society membership
|
Symptoms at diagnosis
|
Specific knowledge about the disease
|
Age at presentation
|
Cognitive restructuring
|
|
Mager et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
x
|
♦
|
♦
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Chauhan et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Anson et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
−
|
−
|
|
Sarkhy et al
|
−
|
−
|
−
|
♦
|
♦
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Ljungman and Myrdal
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Taghdir et al
|
−
|
−
|
−
|
−
|
−
|
x
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Wagner et al
|
−
|
−
|
−
|
x
|
−
|
−
|
x
|
x
|
−
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
|
Charalampopoulos et al
|
−
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
x
|
x
|
♦0
|
−
|
−
|
−
|
−
|
|
Roma et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
♦
|
−
|
−
|
−
|
−
|
|
Khurana et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
MacCulloch and Rashid
|
−
|
♦
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Garg and Gupta
|
♦[1]
|
−
|
−
|
x
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
−
|
♦[1]
|
−
|
|
Personality Related
|
Quality of Life
|
|
Problem-solving
|
Social withdrawal
|
Wishful thinking
|
Resignation
|
Self-blame
|
Less emotional regulation
|
Less distraction
|
Less blaming others
|
Novelty-seeking
|
Persistence
|
Higher HRQOL in physical domains
|
Higher parental perceived QOL in social domains
|
QoL perceived by children
|
QoL (♦diet♦ parameter) evaluated by parents (p = 0,0045)
|
CDDUX score
|
Parents CDDUX
|
|
Mager et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
♦
|
♦
|
−
|
−
|
−
|
−
|
|
Chauhan et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Anson et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Sarkhy et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Ljungman and Myrdal
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Taghdir et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
x
|
|
Wagner et al
|
x
|
x
|
x
|
x
|
x
|
♦
|
♦
|
♦
|
♦
|
♦
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Charalampopoulos et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Roma et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Khurana et al
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
x
|
♦
|
−
|
−
|
|
MacCulloch and Rashid
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
|
Garg and Gupta
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
−
|
Abbreviations: -, not studied; x, not found to be associated with compliance; ♦, found
to be associated with compliance; ◊, associated with noncompliance; 1, established
as a predictor after a logistic regression; 0, not established as a predictor after
logistic regression; CD, celiac disease; GFD, gluten-free diet; HRQOL, health related
quality of life; QoL, quality of life.
Adhesion Assessment
Adhesion was measured heterogeneously between studies. One study[8] (9%) evaluated compliance measuring antitissue transglutaminase antibodies (t-TG)
levels whereas 11 studies[5]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18] (91%) relied on self-reported information with only one verifying it through measurement
of t-TG levels.[18] Self-reported compliance can be divided in questionnaires[5]
[9]
[10]
[12]
[13]
[14]
[15]
[16]
[18] or clinician interviews.[11]
[17] Studies that used questionnaires had designed questionnaires specifically for the
study or relied on previous validated questionnaires. Only one article used biopsies
in follow-up.[17] Despite doing so, the results were neither described nor used in conclusions. No
article reported the use of urine gluten immunogenic proteins in monitoring disease
activity. [Table 6] summarizes these findings.
Table 6
Methods used to access compliance across the study
|
Authors
|
Questionnaire
|
Biopsy
|
Clinical evaluation
|
Anti-TG antibodies
|
EMA
|
Antireticulum antibodies
|
|
Mager et al
|
Applied
|
|
|
Applied
|
|
|
|
Chauhan et al
|
Applied
|
|
Applied
|
|
|
|
|
Anson et al
|
|
Applied
|
Applied
|
|
|
Applied
|
|
Sarkhy et al
|
Applied
|
|
|
|
|
|
|
Ljungman and Myrdal
|
Applied
|
|
|
|
|
|
|
Taghdir et al
|
Applied
|
|
|
Applied
|
Applied
|
|
|
Wagner et al
|
Applied
|
|
|
|
|
|
|
Charalampopoulos et al
|
Applied
|
|
|
Applied
|
Applied
|
|
|
Roma et al
|
Applied
|
|
|
Applied
|
Applied
|
|
|
Khurana et al
|
Applied
|
|
|
|
|
|
|
MacCulloch and Rashid
|
Applied
|
|
|
|
|
|
|
Garg and Gupta
|
Applied
|
|
|
|
|
|
Age
The works evaluating age treat this variable as categorical, dichotomous, and use
different cut offs. Independently of the cut off value, these studies usually consider
two groups, “younger” and “older” children.
In five papers (three of “Good” quality,[11]
[13]
[18] one of “Medium” quality,[14] and one of “Poor” quality[10]), younger age was significantly associated with compliance. In addition, two of
these articles[13]
[14] performed impact analysis, using logistic regression, and showed “older age” contributes
to predict noncompliance. This observation was further supported by another two studies
(one of “Good” quality[15] and one of “Medium” quality[12]) showing older children to be significantly associated with noncompliance. In our
sample, two papers (of “Medium” quality[17] and of “Poor” quality[8]) were unable to report significant differences.
Maternal Education
In our review, eight articles evaluated maternal education. Four articles (two of
“Good” quality[11]
[13] and two of “Medium”[5]
[17] quality) showed maternal education to be a significant factor for compliance to
a GFD while another four (two of “Good” quality[16]
[18] and two of “Poor” quality[8]
[9]) failed to show an effect.
Interestingly, one of the articles reporting an association between maternal education
and compliance to a GFD, after performing a binary multivariate logistic regression
analysis found this factor not to be a predictor of GFD compliance.[13] In agreement, another article (“Good” quality[11]) showed a correlation between lower maternal education and noncompliance to GFD.
Paternal Education
Of the 12 articles included, six analyzed the influence paternal education has on
a child's compliance. Of these, two articles (both of “Medium”[5]
[17] quality) showed paternal education to be a significant factor for compliance to
a GFD whereas another four (two of “Good” quality[13]
[18] and two of “Poor”[8]
[9] quality) failed to do so.
Parental Knowledge of CD
One article (“Good” quality[11]) demonstrated this parameter as positively influencing compliance to GFD while another
(“Medium” quality[17]) found it not to influence it. Interestingly, one report (“Good” quality[14]) distinguishes parental knowledge in perceived and evaluated, showing that only
the first was significantly associated with compliance to GFD. Moreover, after performing
a multiple logistic regression they showed it is a predictor of compliance. At last,
an article (“Good” quality[13]) reported statistical differences between the compliant and noncompliant groups,
concerning parental knowledge of CD but after conducting a binary multivariate logistic
regression analysis, demonstrated this factor was not a predictor of compliance to
GFD.
Family Type
Four articles evaluated “family type” as a dichotomic variable: a nuclear family—in
which only the parents and their children live together, or a joint family—where the
household inhabitants includes other family members. Two papers (“Good” quality[11]
[13]) reported that belonging to a nuclear family increases GFD compliance. In addition,
one of the articles[13] after performing a multivariable logistic regression analysis showed it to be a
predictor of GFD compliance. The remaining two papers (“Medium”[5] and “Poor”[8] quality) showed no differences between compliant and noncompliant groups in relation
to “family type.”
Child's Knowledge of CD
The two works (of “Poor” quality[9]
[10]) that analyzed this variable showed a child's knowledge of CD as positively influencing
compliance to GFD.
Member of Celiac Society
Two articles (one of “Medium”[14] and one of “Poor”[9] quality) evaluating the association between “adherence” and “celiac society membership”
found significant differences between the compliant and noncompliant groups, with
membership increasing GFD compliance. However, in one article, after performing a
multivariate logistic regression analysis the effect was lost.[14]
Quality of Life
Three articles were found concerning the QoL. One article (of “Good” quality[18]) evaluated QoL on four different domains (social, emotional, school, and physical)
and found that higher compliance was related with higher parental, perceived QoL,
in social domains, and with child perceived QoL, in physical domains. Another article
(of “Poor” quality[8]) evaluated QoL based on another scale—socio-demographic, QoL, diet, communication,
and having CD. Using this scale, only the “diet” section as positively influenced
compliance to GFD. Using the same scale, the last article (of “Medium” quality[5]) was unable to find any differences in the overall QoL.
Maintaining GFD
Three papers evaluated the difficulty in maintaining GFD. Two (of “Good”[11]
[13] quality) stated children with higher compliance to the GFD considered gluten to
have a “good taste” and found it less difficult to keep GFD generally at school and
parties/marriages. Moreover, a binary multivariate analysis showed these factors were
positive predictors of compliance.[13] Another article (of “Medium” quality[17]) found that children who reported more difficulty in maintaining GFD were more frequent
on the noncompliant group.
Discussion
Compliance within pediatric age is challenging,[13] hence the importance of finding factors associated with compliance. Overall, our
review showed three main factors associated with GFD compliance, “Family type” and
“Parental knowledge of CD” positively increase GFD compliance while increasing “age”
in pediatric population decreases compliance. In addition, maternal education and
Celiac Society Membership are also related with GFD compliance.
In comparison to other topics regarding CD, little literature can be found regarding
this subject, especially in pediatric populations. Our first literature search was
unable to identify any systematic work on this matter and the first review published
on the topic was on June 4, 2019 by Myléus et al.[19] In this work, Myléus et al[19] reviews the methods used to evaluate GFD compliance and associated risk factors
while we propose to identify specific factors that positively or negatively affect
GFD compliance.
In addition, we found the need to address compliance specifically in CD patients without
comorbidities since some of these, such as diabetes mellitus, imply additional lifestyle
changes and diet restrains.
While it is logical to understand “age” as a having a major role in compliance, our
results confirm this parameter is a good predictor of GFD compliance. As age increases
so does autonomy in food selection. Furthermore, with age, there is also the need
for social integration and peer approval.[13] Also, considering an early age of diagnosis, it is less likely for a patient to
develop unrestricted eating habits. All these are challenging when maintaining a different
lifestyle, such as a GFD. Despite the absence of a cut-off value, there is a general
consensus among the literature as per which changes in compliance are associated with
age.[10]
[11]
[12]
[13]
[14]
[15]
[18] Additionally, two articles demonstrated “older pediatric age” was associated with
prediction of noncompliance. In fact, they stated that with each year of increase
in age, the child had a 25[13] and 15%[14] less chance of remaining compliant to a GFD. Although one work reported opposite
findings, its “Poor” quality limits its relevance to our analysis.[8]
When analyzing children's behavior toward maintaining a GFD, we expected to find differences
between compliant and noncompliant children. Indeed, children that considered “gluten
products as having better taste” displayed better GFD compliance and those reporting
GFD “to be more difficult to maintain” showed less GFD compliance.[11]
[13]
[17] While being quite challenging, as our data shows compliance decreases as children
grow up, it is nonetheless a window of opportunity for pediatricians and dieticians
to intervene by increasing the children's knowledge of CD and, consequently, GFD may
become a more achievable goal. It should be noted that as the ability to “maintain
a GFD” was self-reported, the relation of causality might be misleading so further
investigation is required.
Concerning the effect of maternal education, we would expect this parameter to be
a good predictor of GFD compliance due to the mother's role in food preparation and
nutritional care.[13] However, the results remain controversial as half of the studies found this parameter
to be related to GFD compliance[5]
[11]
[13]
[17] while the remaining did not,[8]
[9]
[16]
[18] highlighting the need for further investigation.
To have a clearer picture on the influence of parental roles and since most works
only study the maternal contribution, when available we also analyzed the influence
of the father's education to GFD compliance. Two “Good” quality studies with large
populations were unable to demonstrate differences in the impact of this parameter
between complaint and noncompliant groups,[13]
[18] although smaller studies of “Medium” quality supported this hypothesis.[5]
[17] According to our results, it is likely this factor is not associated with GFD compliance,
but it should be further explored in future works.
It is important to stress that there is no evidence of correlating parental knowledge
of CD with formal education. Nonetheless, parental knowledge of CD is related with
compliance to GFD in pediatric populations, probably due to the major role that parents
play in choosing their child's diet. In fact, Charalampopoulos et al showed parental
knowledge is a predictor of compliance[14] as children whose parents had a high perceived knowledge on CD were 3.3 times more
likely to follow a strict diet. While this data was also supported by another “Good”
quality work,[11] two others[13]
[17] of identical quality failed to identify it as a predictor of compliance emphasizing
the need for further studies on this subject. Even though generalization is not possible
at this time, physicians could still use parental knowledge of CD as a line of action
to increase GFD compliance. This seems logical since parents with more knowledge will
fail less in making diet choices,[13] therefore their child complies more with a GFD.
Children feeding habits are the result of parental ability to drive their choices.
Also, we report that decrease in compliance relates with older age. Therefore, it
would be worth exploring this shift in their routine, as it comprises a change in
compliance.
The analysis of “family” as a unit shows nuclear families are associated with compliance
to GFD while joint families are related with noncompliance.[5]
[8]
[11]
[13] One work demonstrated children from nuclear families to be four times more likely
to maintain a GFD[13]—an effect thought to be associated with parents being more focused on their child's
routine and environment. In a joint family, the amount of people eating on other diets
may tempt the child to not comply.[13] Nevertheless, two articles were unable to find a relationship between GFD compliance
with the family type.[5]
[8] Given the lower quality of this work, there is a limitation to the relevance of
these findings in our analysis. Importantly, these findings concerned a geographically
limited region[5]
[8]
[11]
[13] limiting its generalization due to potential sociodemographic differences.
One would expect children to be more knowledgeable of CD to be more inclined to be
GFD compliant given their raised awareness of the consequences of nonadherence and
familiarity with gluten-free products. Indeed, two studies[9]
[10] showed children's knowledge of CD to positively influence GFD compliance, however,
due to the small population size evaluated, the overall quality of these reports is
poor and the vague definition of “knowledge in CD,”[10] extrapolation is limited.
Celiac Society Membership per se is positively related with compliance,[9]
[14] which in light of our data are probably due to increased availability of information
and contact with other CD patients. Importantly, the extent of its importance decreases
with increasing levels of parental knowledge and with increased age of pediatric patients.
It is important to note that only two studies demonstrated this factor as influencing
compliance,[9]
[14] one of them having “Poor” quality.[9] Also, these results were based on specific populations[9]
[14] (Greek), and therefore a selection bias may be present which partially limits its
extrapolation to other populations.
High heterogenity is observed regarding QoL. This is due to the high variability of
tools used to assess it and to the inconsistency of the studies overall quality. Therefore,
is not possible to draw conclusions concerning this parameter.
Several factors limited our analysis. First, the heterogeneity of the tools used to
measure GFD compliance leads to inconsistent results between reports. Standardization
of research protocols would greatly enhance the quality and validity of future studies.
Also, without having an objective measurement, such as t-TG levels, it is difficult
to exclude contaminations.
Second, the definition of “GFD compliance” needs to be clarified. In the studies herein
included, compliance was broadly defined as “a dichotomous variable in which a positive
outcome is identifiable as the absence of awareness of gluten intake.” By contrast,
any awareness level of transgression to a GFD was considered as noncompliance. Our
findings are corroborated by Myléus et al[19] since they also could not find any method more reliable to assess compliance.
Third, most studies rely on parental information alone; which by itself is a potential
source of bias since patients themselves do not report data. Of course, given the
specific particularities of this population, it might not have been possible to obtain
the data otherwise.
Fourthly, an additional source of bias was associated with the lack of standardization
in the age categories at study. The lower and higher limits of each age group varied
greatly between reports, compromising its evaluation. Finally, there was an overall
lack of quality in what concerns study design and the presentation of results.
As to the reports' quality assessment and subsequent extrapolation of results, we
would like to note that since the majority of the studies were cross-sectional, observational
by nature, the results obtained could not be standardized as predictors, as the relationship
between exposure and outcome cannot be fully discriminated. For this same reason,
in the quality assessment, most studies consistently received a negative score for
the study design. Additionally, we stress the need for further studies that establish
a correlation between exposure and outcome.
Conclusion
Undoubtedly, GFD is strongly related with social and environmental contexts. The interconnection
between parental features and children outcomes became clearer. Despite some of them
being unchangeable, such as age or family type, with this work, we were able to show
evidence that modifiable factors, parental knowledge on CD per example, can also play
major roles in compliance. Nevertheless, the causality between these factors and compliance
still remains unclear. Therefore, the need for further knowledge in causality relations
is in order so that compliance rates, among pediatric populations, can be increased.
Regarding this, age was proved to influence compliance as young children consistently
display better compliance rates. More so, children of informed parents and a nuclear
family household were independently positive influencers of compliance. All these
predictors should be taken into account in clinical practice when evaluating CD patients.
Lastly, it is important to state that a systematic approach to compliance should be
established, only then GFD compliance will be fully understood.
