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Children's eating behavior, feeding practices of parents and weight problems in
early childhood: results from the population-based Generation R Study
International Journal of Behavioral Nutrition and Physical Activity 2012,
Pauline W Jansen (firstname.lastname@example.org)
Sabine J Roza (email@example.com)
Vincent WV Jaddoe (firstname.lastname@example.org)
Joreintje D Mackenbach (email@example.com)
Hein Raat (firstname.lastname@example.org)
Albert Hofman (email@example.com)
Frank C Verhulst (firstname.lastname@example.org)
Henning Tiemeier (email@example.com)
26 January 2012
24 October 2012
30 October 2012
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Children's eating behavior, feeding practices of
parents and weight problems in early childhood:
results from the population-based Generation R
Pauline W Jansen1,2,*
Sabine J Roza2,3
Vincent WV Jaddoe1,4,5
Joreintje D Mackenbach2
Frank C Verhulst2
1 The Generation R Study Group, Erasmus MC-University Medical Center
Rotterdam, Rotterdam, the Netherlands
2 Department of Child & Adolescent Psychiatry / Psychology, Erasmus MC-
University Medical Center Rotterdam, PO-BOX 2060, Rotterdam 3000 CB, The
3 Department of Psychiatry, Erasmus MC-University Medical Center Rotterdam,
Rotterdam, the Netherlands
4 Department of Epidemiology, Erasmus MC-University Medical Center
Rotterdam, Rotterdam, the Netherlands
5 Department of Pediatrics, Erasmus MC-University Medical Center Rotterdam,
Rotterdam, the Netherlands
6 Department of Public Health, Erasmus MC-University Medical Center
Rotterdam, Rotterdam, the Netherlands
* Corresponding author. Department of Child & Adolescent Psychiatry /
Psychology, Erasmus MC-University Medical Center Rotterdam, PO-BOX 2060,
Rotterdam 3000 CB, The Netherlands
Weight problems that arise in the first years of life tend to persist. Behavioral research in this
period can provide information on the modifiable etiology of unhealthy weight. The present
study aimed to replicate findings from previous small-scale studies by examining whether
different aspects of preschooler‟s eating behavior and parental feeding practices are
associated with body mass index (BMI) and weight status -including underweight,
overweight and obesity- in a population sample of preschool children.
Cross-sectional data on the Child Eating Behaviour Questionnaire, Child Feeding
Questionnaire and objectively measured BMI was available for 4987 four-year-olds
participating in a population-based cohort in the Netherlands.
Thirteen percent of the preschoolers had underweight, 8% overweight, and 2% obesity.
Higher levels of children‟s Food Responsiveness, Enjoyment of Food and parental
Restriction were associated with a higher mean BMI independent of measured confounders.
Emotional Undereating, Satiety Responsiveness and Fussiness of children as well as parents‟
Pressure to Eat were negatively related with children‟s BMI. Similar trends were found with
BMI categorized into underweight, normal weight, overweight and obesity. Part of the
association between children‟s eating behaviors and BMI was accounted for by parental
feeding practices (changes in effect estimates: 20-43%), while children‟s eating behaviors in
turn explained part of the relation between parental feeding and child BMI (changes in effect
This study provides important information by showing how young children‟s eating
behaviors and parental feeding patterns differ between children with normal weight,
underweight and overweight. The high prevalence of under- and overweight among
preschoolers suggest prevention interventions targeting unhealthy weights should start early
in life. Although longitudinal studies are necessary to ascertain causal directions, efforts to
prevent or treat unhealthy child weight might benefit from a focus on changing the behaviors
of both children and their parents.
Overweight, Underweight, BMI, Eating behavior, Feeding, Parenting, Children
Weight problems in childhood and adolescence are very common in Western countries with
overweight rates estimated at 17-25% in West-Europe, Australia, and the United States [1-3].
Underweight is less prevalent than overweight but an estimated 3-8% of children in
developed countries have underweight [4,5]. Childhood under- and overweight are an
important public health problem, as these conditions tend to have a chronic character
(underweight ; overweight [7,8]) and predict a wide range of future morbidity. Overweight
in children is associated with future cardiovascular diseases [8,9], diabetes , and
psychosocial problems [7,11]. Furthermore, even though thinness is nowadays likely to
represent the lower end of the healthy weight distribution , there is also evidence that a
low body mass index (BMI) in early childhood is a risk factor for later coronary heart disease
 in Western populations.
Against the background of the common occurrence and chronic course of childhood weight
problems it is important to advance our knowledge of their etiology. Several risk factors for
childhood overweight have been identified, such as parental weight status, early growth and
children‟s physical activity and sedentary behavior, with some of these risk factors seemingly
easier modifiable than others [13,14]. Behavioral research also provides information on the
modifiable etiology of weight problems and suggested that children‟s eating behavior and
appetite-related traits are associated with BMI [15,16]. Moreover, it has been shown that
parents exert an important influence on children‟s eating patterns and weight development
through their own eating behaviors and feeding practices [17,18]. This evidence is mainly
based on studies in school-aged children and adolescents [15-18], while it has been argued
that weight problems can already arise earlier in life [19,20]. The first few years of life are
characterized by rapid growth and encompass several critical periods in children‟s growth
trajectories . Moreover, young children go through remarkable transitions in digestive
behavior, and evidence points to children‟s eating behaviors being established by the end of
the preschool period and remaining stable thereafter . This makes preschool children a
particularly important target group for interventions aimed at enhancing healthy eating
behaviors and a healthy weight. Given the stability of eating behaviors and appetitive traits
across early and later childhood [22-24], we hypothesized that the relation between eating
behavior and weight status does not differ substantially between the different age groups.
However, there is a need to confirm associations among young children before evidence-
based interventions aimed at the prevention and worsening of unhealthy child weight can be
Considering the importance of the early developmental period, researchers started attempting
to identify behavioral influences on BMI in preschoolers such as parental feeding practices.
Parental pressure on children to eat was negatively related to child BMI [25-28], while
parents‟ restrictions regarding food intake was positively associated with children‟s weight
[27,29]. This behavior of parents can be a response to children‟s weight status, but parental
feeding practices also elicit certain child eating behaviors that in turn may influence weight
development. However, several other studies have not been able to replicate these findings
[25,26,28,30,31]. Moreover, other dimensions of parental feeding, like control and
monitoring, were hardly associated with preschoolers‟ BMI [25-28,30-33].
Eating behaviors of young children, such as eating in response to environmental food cues,
increase the likelihood of children to have a high BMI [25,29], while responsiveness to
internal satiety cues and pickiness have been associated with a lower mean BMI [15,34].
Again, these associations were not consistently found [25,26,35,36]. The lack of findings
between children‟s eating behaviors and BMI, but also between parental feeding practices
and child BMI, could well be due to limited statistical power. In contrast to several studies
examining these associations in older children e.g [16,37,38],. research in preschool children
was mainly conducted in small samples including less than 300 children [25-27,29-33,35,36],
with a few exceptions [15,28,34]. Moreover, research in this field was hampered by the use
of high-risk groups, such as children at risk of overweight or from low-income families
[26,27,32,33,35]. This limits generalizibility of results, as associations might be different at
the population level. Findings of several earlier studies should also be interpreted with
caution as parent reports of children‟s anthropometrics were used [15,25,35,36]. Parents tend
to underestimate their child‟s weight, especially if the child is overweight or obese , and
many children with overweight might be missed. Finally, although several studies had
information available on both children‟s eating behaviors and parental feeding practices
[25,26,29,35], it remains largely unknown if eating behavior of children and feeding behavior
of parents have an independent effect on child BMI or whether these behaviors partly account
for each others effect on child BMI. There is some evidence for the latter: Joyce and
colleagues showed that preschool children‟s disinhibited eating – a composite score of food
responsiveness and emotional overeating – partially mediated the association between
parental restriction and children‟s BMI . Research in school-aged children also suggests
complex associations between parental behavior, and children‟s eating and BMI [40,41].
These studies hypothesized a child-responsive model postulating that child characteristics
influence parental behavior .
The present study aims to replicate findings of previous behavioral studies in preschool
children by examining whether young children‟s eating behavior and parental feeding
practices are associated with objectively measured BMI in a large population-based cohort of
four-year olds. Different food approach and food avoidant behaviors of children, as well as
three different parenting dimensions will be examined. Moreover, not only overweight and
obesity, but underweight will be studied as well. Childhood underweight is a highly
understudied area of behavioral research despite the evidence that this condition is a risk
factor for future morbidity just like overweight . Based on previous studies, we
hypothesized that children with high levels of food approach behaviors like food
responsiveness have a higher mean BMI, and that food avoidant behaviors such as satiety
responsiveness and fussiness are associated with a lower mean BMI. Consistent with a child-
responsive model , we also expected that parents of children with overweight or high
levels of food approach behaviors are more restrictive. These parents would also exert less
pressure on their children to eat than parents of children with a normal weight or with high
levels of food avoidant behaviors. Finally, we hypothesized that eating behavior of children is
associated with BMI independently of parental feeding practices. In accordance with a child-
responsive model , we also expected that the relation between parental feeding and child
BMI is fully explained by children‟s eating behaviors.
Design and study population
This study was embedded in Generation R, a population-based cohort from fetal life onwards
. Briefly, all pregnant women living in Rotterdam, the Netherlands, with an expected
delivery date between April 2002 and January 2006 were invited to participate (participation
rate: 61%). The ethnic distribution of participants differed only moderately from that of the
population in the study area . However, mean household income and educational
attainment were slightly higher among study participants. Written informed consent was
obtained from all participants. The Medical Ethical Committee of the Erasmus Medical
Center, Rotterdam, has approved the study. Information of the participants was obtained by
postal questionnaires filled out by parents, and from medical records of hospitals, midwives,
and Child Health Centers. Full consent for the postnatal phase of the Generation R Study was
obtained from 7295 children and their parents. For 4987 of these children, data on at least one
of the subscales of eating behavior was available. The population per analyses varied slightly
per subscale due to missing data on subscales (n between 4911 and 4967). Information on
BMI was available for 3157 children.
Comparison of non-responders (n = 2308) and responders (n = 4987) indicated that data on
eating behavior was more often missing in children of non-Dutch origin, χ2(1, 6738) = 414, p
< .001, with a higher BMI, F(1, 4206) = 11, p = .001, with lower educated mothers, χ2(1,
6557) = 497, p < .001, and higher maternal BMI, F(1, 6521) = 55, p < .001, as compared to
children with complete data on eating behavior. In contrast, among the children with
available data on eating behavior (n = 4987), children with (n = 3157) and without (n = 1828)
data on BMI did not differ from each other with respect to national origin, χ2(1, 4803) = 3, p
= .085, maternal educational level, χ2(1, 4715) = 0.1, p = .724, or maternal BMI, F(1, 4440) =
0.08, p = .782, suggesting that data on BMI was missing at random.
Children’s eating behavior
Eating behavior was assessed by postal questionnaire including the Child Eating Behaviour
Questionnaire (CEBQ) and Child Feeding Questionnaire (CFQ). Parents were asked to fill
out these questionnaires around the fourth birthday of their child. The translation of the
original English questionnaires was carried out using a standard forward-backward
translation method .
The CEBQ  is a 35-item instrument designed to assess variation in eating style among
children. The CEBQ consists of seven subscales, four of which measure food approach
behaviors: Emotional Overeating, Enjoyment of Food, Food Responsiveness, and Desire to
Drink. The other three subscales quantify food-avoidant behavior: Emotional Undereating,
Satiety Responsiveness, and Fussiness. Examples of items are “My child loves food”
(Enjoyment of Food), “Even if my child is full up, s/he finds room to eat his/her favorite
food” (Food Responsiveness), “My child eats less when upset” (Emotional Undereating), and
“My child has a big appetite” (Satiety Responsiveness). The CEBQ has good psychometric
properties, such as good internal consistency, concurrent validity with actual eating behavior,
test-retest reliability, and stability over time [34,44-46]. Good internal consistency was
confirmed in our sample with Cronbach alpha‟s ranging from.78 to .89.
Three subscales of the CFQ  were used to assess parental attitudes and strategies
regarding control of children‟s eating: Monitoring (3 items), Restriction (8 items), and
Pressure to Eat (4 items). Examples of items are “How much do you keep track of the high
fat foods your child eats?” (Monitoring), and “I intentionally keep some foods out of my
child‟s reach” (Restriction). Research provided evidence for concurrent validity of the CFQ
with actual observations of feeding behavior of mothers . Furthermore, the CFQ-scales
correlate well with children‟s actual food intake  and children‟s BMI in two small scale
samples  indicating high external validity. Reliability of the administered CFQ-scales was
moderate (α = .66, Pressure to Eat) to high (α = .92, Monitoring).
CEBQ and CFQ items were answered on a five-point Likert scale from 1=never to 5=always.
Scale scores were only calculated if at least 75% of the items were completed. The
continuous CEBQ and CFQ scale scores were expressed as standard deviation scores to
facilitate effect size comparison between scales.
Trained staff of the municipal Child Health Centers obtained children‟s growth
characteristics as part of a routine health care program. Children visit the centers on a regular
basis and the present study uses data from the visit scheduled around the fourth birthday.
Weight was measured by a mechanical personal scale (SECA®) while children were wearing
underwear only. Height was measured in standing position by a Harpenden stadiometer
(Holtain Limited®). Body Mass Index (BMI) was calculated as weight/height2 (kg/m2). Age-
and sex-specific BMI standard deviation scores were calculated using the Dutch reference
 in the Growth Analyzer program (http://www.growthanalyser.org). International age-
and sex-specific cut offs were used to classify children into four different weight groups:
underweight , normal weight, overweight and obesity .
Several child and parental characteristics were considered as possible confounders, as they
were previously linked with children‟s BMI and eating behaviors [14,47,52]. Information
about child gender, date of birth (to calculate age), and birth weight were obtained from
midwife and hospital registries. National origin of the child was based on country of birth of
both parents, as assessed by parental questionnaire. Mothers also reported in postal
questionnaires about educational level, family income, smoking habits during pregnancy and
global psychopathology, which was assessed with the Brief Symptom Inventory .
Paternal psychopathology was assessed using the same instrument in a separate questionnaire
filled out by the fathers. Height and weight were measured in mothers and fathers at the
Generation R research centre. Parental BMI was calculated as weight/height2.
The distribution of confounders is presented stratified by weight status. The χ2-statistic was
used to test whether the distribution of categorical covariates differed between the weight
categories; ANOVA‟s were used for continuous covariates, and Kruskal-Wallis tests for
continuous non-normally distributed covariates. The association between the CEBQ, CFQ
and child weight was first explored with Pearson‟s correlation coefficients. Effect sizes of
Pearson‟s correlation are interpreted as small for r around 0.10, medium for r around 0.30,
and large effect size for r of 0.50 and higher according to Cohen‟s criteria . Then,
regression analyses were conducted to examine the relationship between CEBQ, CFQ and
child weight in-depth. Linear regression analyses were performed to estimate the association
of eating behavior with the continuous outcome BMI standard deviation scores. Three
different models are presented: the first model shows the unadjusted results; the second
model is confounder-adjusted; and in the third model the child eating behavior and parental
feeding practices are mutually adjusted. Thus, in these analyses the CEBQ-scales are adjusted
for the CFQ-scales, while the CFQ-scales are adjusted for the CEBQ-scales. Next,
multivariate multinomial logistic regression analyses were conducted to calculate children‟s
risk for being underweight, overweight or obese as compared to children with a normal
weight. Finally, sensitivity analyses were conducted to test the robustness of our findings. In
the first sensitivity analysis, we aimed to estimate whether the used cut-off for underweight
that resulted in a fairly high percentage of children with underweight influenced our results.
We repeated the multinomial logistic regression analyses with underweight defined using
stricter cut-offs, i.e. based on a BMI of one or two standard deviations below the mean. In the
second part of the sensitivity analyses, to evaluate whether imputation of missing values on
child BMI influenced our findings, the linear and multinomial logistic regression analyses
were repeated in the subsample of 3157 children with data on BMI available.
Missing values on child BMI (n missings=1828) and the confounders (n missings ranged
from 4 in birth weight to 1301 and 1743 for paternal BMI and psychopathology, respectively)
were estimated using multiple imputation techniques . All variables included in the
multivariate regression analyses as well as available information on child BMI at younger
ages were used to estimate missing values . The regression analyses were performed on
the imputed datasets (n = 4987) and the reported effect estimates are the pooled results of five
imputed datasets. All statistical analyses were performed using SPSS version 17.0.
Characteristics of the children and their parents are presented in Table 1. The majority of the
children included in the study population (78%) had a normal weight. At age four years, 13%
of the children had underweight, 8% overweight, and 2% obesity. Children with underweight,
overweight or obesity were more often of non-Dutch origin than children with a normal
weight, χ2(6, 3044) = 58, p < .001. No gender differences were found in weight status of the
children, χ2(3, 3072) = 8, p = .057. Mothers of children with obesity were more often lower
educated, χ2(1, 2388) = 22, p < .001, and had a higher mean BMI, F(1, 2229) = 478, p < .001,
than mothers of children with a normal weight.
Table 1 Population characteristics according to the weight status of the children
Gender (% boy) 50.1
National origin (%): Dutch 66.7
Other Western 9.3
Birth weight (grams) 3444 (567)
Family income (%)$:
>2200 euro 67.3
<2200 euro 32.7
BMI mother (weight/length2) 24.4 (4.1)
BMI father (weight/length2) 25.2 (3.3)
Global psychopathology mother (score) 0.13 (0–2.8)
Global psychopathology father (score) 0.06 (0–3.4)
Values are percentages for categorical, means (SD) for birth weight and BMI, and medians
(100% range) for psychopathology score. #n = 3157, as this table represents unimputed data.
¶p indicates statistical significance of between-group differences.
dichotomized for the purpose of this table only and included in the analyses as follows:
education (low, mid-low, mid-high, high), income (<1200, 1200–2200, >2200 euro‟s per
month), and smoking (non-smoking, until pregnancy was known, continued smoking)
Weight status of children#
n = 2473
n = 239
n = 48
n = 397
High 57.5 54.2
$ Covariates were
Table 2 shows that correlations of all CEBQ- and CFQ-scales, except Emotional Overeating,
Desire to Drink and Monitoring, with children‟s BMI represented small to medium effect
sizes. All eating behavior scales were significantly correlated with at least one of the feeding
practices scales, although most of these associations were rather small, e.g. Monitoring and
Fussiness, r = −.038, p < .001. Medium effect size correlations were found for Food
Responsiveness and Restriction, r = .266, p < .001, Enjoyment of Food and Pressure to Eat, r
= −.338, p < .001, and for Satiety Responsiveness and Pressure to Eat, r = .404, p < .001.
Correlations between the CEBQ subscales (data not shown) indicated mostly small to
medium effect sizes, e.g. Emotional Overeating and Emotional Undereating, r = .277, p <
.001, and large correlations were found between the subscales Saturation Responsiveness,
Enjoyment of Food and Fussiness (all r > .450, p < .001). The CFQ-scales were only weakly
correlated with each other (all r < .200, p < .001).
Table 2 Correlations between the CEBQ scales, CFQ scales and child BMI SD scores
BMI SD scores
Children‟s Eating Behaviour
Enjoyment of Food
Desire to Drink
** p < .001, * < .05
Pearson correlation coefficients
Child Feeding Questionnaire
BMI SD scores Monitoring Restriction
Pressure to Eat
-.186 ** .087 **
In Table 3, linear associations of CEBQ and CFQ with BMI standard deviation (SD) scores
are shown. The eating behavior scales Food Responsiveness and Enjoyment of Food were
associated with higher BMI SD scores of children. These associations attenuated only slightly
and remained highly significant after adjustment for possible confounding factors, such as
maternal BMI and indicators of family socioeconomic status. The CEBQ food avoidant
scales had a negative relation with children‟s BMI SD scores. Again, these associations
remained statistically significant in the adjusted analyses. For instance, a one standard
deviation higher score on Satiety Responsiveness was associated with a 0.23 lower BMI SD
scores, p < .001, in the unadjusted analyses, and with a 0.21 lower BMI SD scores, p < .001,
adjusted for measured confounders. Associations of Emotional Undereating, Satiety
Responsiveness, and Food Responsiveness with children‟s BMI SD scores attenuated about
20% after adjustment for CFQ-scales, while the parental feeding practices explained 43% of
the relation between Fussiness and BMI SD scores (attenuation from Bmodel 2 = −0.07 to Bmodel
3 = −0.04, see Table 3).
Table 3 Association of child eating behavior and eat-related parenting with children‟s
BMI SD scores
Model 1: unadjusted
CEBQ (per SD)
B (95% CI)
−0.10 (−0.13, -0.07)
−0.23 (−0.26, -0.20)
−0.08 (−0.12, -0.05)
0.02 (−0.01, 0.05)
Food Responsiveness 0.23 (0.19, 0.26)
Enjoyment of Food 0.14 (0.11, 0.18)
Desire to Drink
0.02 (−0.01, 0.06)
CFQ (per SD)
−0.02 (−0.05, 0.02)
Restriction 0.09 (0.07, 0.12)
Pressure to Eat
−0.18 (−0.21, -0.15)
# Model 2: adjusted for child gender, national origin, birth weight, age at questionnaire and
BMI assessment, maternal educational level, family income, smoking during pregnancy, and
maternal and paternal BMI and psychopathology. ¶ Model 3: model 2 additionally adjusted
for CFQ-scales (analyses with CEBQ as determinant) or CEBQ-scales (analyses with CFQ as
BMI standard deviation scores
B (95% CI)
−0.08 (−0.10, -0.05)
−0.21 (−0.24, -0.18)
−0.07 (−0.10, -0.04)
0.21 (0.18, 0.24)
0.15 (0.11, 0.18)
0.09 (0.07, 0.12)
−0.17 (−0.20, -0.14)
Model 3 ¶
B (95% CI)
−0.06 (−0.09, -0.04)
−0.17 (−0.21, -0.14)
−0.04 (−0.07, -0.01)
0.17 (0.13, 0.21)
0.10 (0.06, 0.14)
0.06 (0.04, 0.09)
−0.09 (−0.12, -0.06)
Of the CFQ scales, Restriction was positively and Pressure to Eat negatively related with
child BMI SD scores. Parental Monitoring was not associated with child BMI. Children‟s
eating behaviors accounted for a substantial part of the associations between Restriction and
child BMI SD scores (33%), and between Pressure to Eat and BMI SD scores (47%),
although both scales remained significantly associated with children‟s BMI SD scores.
Table 4 presents the relation of CEBQ, CFQ and risk of underweight, overweight and obesity
adjusted for measured confounders. The trends show a similar pattern as the linear
associations presented in Table 4. For instance, children with higher scores on Food
Responsiveness were relatively less often underweight, and more often overweight or obese
than children with lower scores, p for trend < .001. A one standard deviation higher score on
this scale was associated with a more than two-fold risk of being obese (OR = 2.17, 95% CI,
1.77-2.65). All assessed CEBQ and CFQ scales, except Emotional Overeating, Desire to
Drink, and parental Monitoring were highly associated with children‟s weight status.
Table 4 Eating behavior and risk of underweight, overweight and obesity
OR for weight status of children (95% CI)#
CEBQ (per SD)
n = 645
Fussiness 1.10 (0.99-1.22)
Emotional Overeating 0.97 (0.87-1.08)
Enjoyment of Food
Desire to Drink 1.03 (0.92-1.14)
n = 3877
n = 400
n = 65
p for trend
CFQ (per SD)
Pressure to Eat
# Analyses adjusted for child gender, national origin, birth weight, age at questionnaire and
BMI assessment, maternal educational level, family income, smoking during pregnancy, and
maternal and paternal BMI and psychopathology
Sensitivity analyses indicated our findings were fairly robust. First, the results of the logistic
regression analyses were largely unchanged when underweight was defined using stricter cut-
offs, i.e. based on the lowest BMI decile (10.3% underweight) or on a BMI of two standard
deviations below the mean (1.3% underweight). Some of the associations using the more
stringent cut-off, however, did not reach statistical significance due to smaller numbers of
underweight children (e.g. Food Responsiveness OR = 0.75, 95% CI, 0.50-1.12). Second, the
linear and multinomial logistic regression analyses were repeated in the subsample of 3157
children with data on BMI available. Again, the results of these analyses were very similar to
the results presented in Tables 3 and 4 (e.g. Table 4, Fussiness: p-value for trend 0.006 in
unimputed data and 0.001 in imputed data) indicating that imputation of missing values on
child BMI hardly influenced our findings.
This large population-based study among four-year-olds showed that young children‟s eating
patterns and feeding practices of parents are strongly associated with children‟s BMI. Not
only children with overweight but underweight children also had different eating behaviors
than children with a healthy weight. Furthermore, analyses with feeding practices of parents
showed a fairly graded association across the whole range from children‟s underweight to
overweight and obesity. The direction of the reported associations are much in line with
previous findings among older children in the primary school-ages [15-18,37,38] suggesting
an early age onset of relationships between eating behavior, parental feeding and child BMI.
Our observations were largely unaffected by known predictors of unhealthy weight in
childhood, such as low socioeconomic background, national origin and parental weight
status. As expected, associations between eating behavior and BMI of children attenuated,
but persisted after controlling for parental feeding practices. Thus, part of the association
between children‟s eating behaviors and BMI was due to relations between parental feeding
practices and child BMI, suggesting complex associations between these variables. Although
we hypothesized that parental feeding practices would be associated with child weight
entirely through its effect on child eating behaviors, our results showed that feeding styles
were related to offspring BMI even after adjustment for children‟s eating behavior. Possibly,
parental feeding is associated with child BMI through other dimensions of child eating
behavior, such as loss of control or binge eating. However, as a wide range of child eating
behaviors was examined, our findings suggest that the behaviors of children and their parents
are independently associated with children‟s BMI.
Before the results can be discussed, it is essential to consider the reported prevalence rates
first. In our study population, approximately one out of ten children was overweight or obese.
Although this percentage is lower than the global prevalence estimates of overweight in
childhood and adolescence [1-3], it is consistent with the general notion that overweight is
somewhat less prevalent among preschoolers as compared with older children .
Furthermore, the 2% of children with obesity in our study is very comparable with a recent
representative Dutch study reporting obesity prevalence rates of 1% and 3% for 4 year old
boys and girls, respectively . However, the reported overweight rates (11%; boys 8%,
girls 14%) in this nation-wide study were somewhat higher than those observed in our study
(8%). Possibly, children with low socioeconomic background were somewhat
underrepresented in our more urban sample, this may account for a slightly lower prevalence
of overweight, as children from families with lower socioeconomic status are at risk of
About 13% of the four-year-olds in our study were underweight, which is a higher prevalence
estimate than previously shown in school-aged children [4,5]. However, the prevalence rates
of underweight are less established than overweight and obesity rates, particularly in early
childhood. An alternative explanation for differences in prevalence of underweight might lie
in the observation that, especially in girls, the prevalence of underweight is increasing .
As hypothesized, children‟s food approach behaviors Food Responsiveness and Enjoyment of
Food were positively related to children‟s BMI. These scales address children‟s general
appetite for food with Enjoyment of Food measuring normal variation in general appetite,
while the Food Responsiveness scale is designed to detect more dysfunctional levels of
appetite such as the tendency to continue eating if given the opportunity. It has been
suggested that these food approach behaviors become more apparent as children get older and
can make more independent choices about food , but we observed substantial variability
in these traits already in preschoolers. This confirms findings from earlier studies focusing on
overweight [15,25,29], and adds to the current literature that underweight children also had
relatively low levels on Enjoyment of Food and Food Responsiveness. These relations
between appetite and the BMI spectrum might be explained by genetic variants contributing
to both children‟s weight status and their susceptibility to eating in response to the presence
of foods . Genes can exert a direct influence on child behavior and weight status, but can
also work indirectly through the early food environment that is primarily provided by the
parents. For instance, overweight parents might provide an obesogenic eating environment
which stimulates appetite and food intake in the offspring, while relatively lean parents may
discourage the overconsumption of food. However, behavioral genetics of child eating
patterns are relatively understudied and future research is needed to clarify the interplay
between genetic and environmental influences on children‟s eating and weight development
In contrast to what we hypothesized, we found no evidence that the food approach scales
Desire to Drink or Emotional Overeating were associated with child BMI. The findings with
Desire to Drink replicates results from previous studies for which the authors argued that the
lack of finding an association between drinking and weight might have been due to limited
statistical power [26,36]. Apparently, being a thirsty person or the amount of drinking per se
is not related with child BMI. The type of beverages, i.e. the consumption of high-energy
drinks, probably has more influence on weight status . Regarding eating in response to
emotional cues, it has been suggested that the food approach scale Emotional Overeating
reflects the opposite of the food avoidant Emotional Undereating . However, in our study,
we found a positive correlation between the two scales. Moreover, we showed an association
between emotional undereating and BMI, while surprisingly, emotional overeating was not
related with weight status in these very young children. Emotional distress may lead to
inhibition of appetite, but does not result in food craving in young children, suggesting that
these emotional eating behaviors cannot be simply seen as two extremes of the same
continuum. Alternatively, the children in the present study might have been too young to
exhibit excessive eating and snacking, as they probably do not have free access to foods yet.
This hypothesis is substantiated by previous studies showing that increasing BMI was
associated with progressively higher levels of emotional overeating among school-aged
In line with our hypotheses, not only Emotional Undereating, but the food avoidant scales
Satiety Responsiveness and Fussiness were also associated with progressively lower weights
in children. This finding for Fussiness contrasts with previous studies [25,35,36]. However,
in a population-based sample of 1498 Canadian preschoolers, Dubois and colleagues also
reported that picky eaters were more likely to be underweight . Our findings and this
Canadian study suggest that fussiness is indeed associated with a relatively low BMI in the
general population. Possibly, underweight of children leads to higher levels of fussiness, for
instance through an adverse effect of control or pressure of parents on children‟s eating.
However, the analyses substantiate this reasoning only to some extent, as the relation
between fussiness and BMI attenuated but remained statistically significant after adjusting for
parental pressure to eat and monitoring. Thus, it seems likely that at least part of the
association is from pickiness leading to insufficient food intake, which eventually hinders
adequate weight gain and growth. Although the CEBQ refers to fussiness about food in
general, it is also possible that the food intake of picky children is not diverse enough and
lacks essential nutrients like vitamins, minerals, proteins and fibres. Clearly, parents and
primary health care professionals should carefully monitor fussy children and their food
intake, although causal directions have to be ascertained in longitudinal studies.
A negative association between satiety response and BMI in preschoolers was reported once
before . We extend this previous study by showing that both children with overweight
and children with underweight have a different satiety response than children with a normal
weight. Possibly, some young children have a suboptimal down regulation of their food
consumption resulting in excessive weight gain, while other children have a too effective
satiety response resulting in underweight. However, that parental feeding practices accounted
for part of this association suggests more complex pathways. Parental pressure to eat might
reflect a mediation effect, as toddlers who are highly responsive to internal satiety cues and
quickly feel full might be pressured by their parents to eat more, which can be
counterproductive and actually result in less eating . Alternatively, restrictions of parents
regarding food intake could result in a poor responsiveness to internal hunger and satiety
cues, thereby influencing children‟s food intake and weight gain.
As hypothesized, restrictive parenting during mealtimes was positively and parental pressure
to eat was negatively associated with children‟s BMI. Within the framework of a child-
responsive model, these feeding strategies can be interpreted as a response to child weight:
parental efforts to restrict food intake may be a response to children‟s overweight, while
parents of children with underweight probably pressure their children to eat more. However,
the observed associations are probably more complex. It is not possible to infer causality
from our cross-sectional study, but the findings suggest a number of explanations. Parental
restriction was correlated to children‟s Food Responsiveness, and child eating behavior
attenuated the association between restriction and child BMI. This suggests that restrictive
parenting might stimulate poor intake regulation and overeating at times when access to food
is not restricted, eventually resulting in weight gain. Parental pressure to eat may be
associated with child weight through a counterproductive effect of lowering children‟s
enjoyment of food, eventually resulting in eating less and weight loss. Alternatively, pressure
to eat might also be a parent‟s response to children quickly feeling „full‟. This explanation is
substantiated by the correlation between Pressure to Eat and CEBQ Satiety Responsiveness.
Clearly, longitudinal research with repeated measurements of children‟s eating behavior,
feeding practices of parents and child BMI is needed to further unravel these pathways.
We found no evidence that parental monitoring of children‟s food intake is associated with
child BMI, which is in line with previous studies using small convenience samples
[25,26,28,30-33]. Perhaps, keeping track of the amount of sweets, snacks and high-fat food
children consume is a very common behavior of parents, not necessarily related to children‟s
BMI. Alternatively, parents might have provided socially desirable answers on the
Some limitations of this study have to be discussed. Firstly, a number of children had no
information on eating behavior or BMI. While missing data on BMI was rather random,
information on eating behavior was more complete in Dutch children of relatively high
educated mothers. However, although this selective response may have influenced the
reported prevalence estimates, it probably has had less effect on the associations reported in
our study . Secondly, although children‟s anthropometrics were measured objectively,
assessments of problematic eating behaviors were based on mothers‟ subjective opinions of
children‟s behavior. Even though the analyses were adjusted for several maternal
characteristics, it cannot be ruled out completely that a mother‟s well-being and her attitudes
about health influenced her ratings of children‟s eating behavior. On the other hand,
validation studies indicated that parent reports of children‟s eating behaviors, such as the
CEBQ and CFQ, correlated substantially with children‟s actual food intake [34,62]. Another
limitation is the study‟s cross-sectional design which precludes inferences about causation.
Longitudinal studies are essential to detect whether feeding practices of parents and
children‟s eating behaviors predict the development of weight problems, or if they are
associated concurrently only.
In a large population-based sample, we showed that food responsiveness, enjoyment of food
and parental restriction are associated with progressively higher weights of children. The
findings regarding these food approach behaviors of children are especially worrisome in the
context of the current, rather obesogenic environment , as such settings place children
who are interested in food at risk for developing overweight. Furthermore, our study showed
that children with underweight have distinct eating behaviors and that their parents are more
likely to pressure during mealtimes. The associations between preschoolers‟ eating behavior,
parental feeding patterns and child BMI are complex and need further investigation.
Meanwhile, health care professionals should be aware that there is a complex interplay
between children and their parents regarding eating, and that the behaviors of both children
and their parents are to some extent independently associated with child BMI. This implies
that if behaviors are indeed causally related to child BMI – which seems quite plausible –
efforts to prevent or treat unhealthy child weight might benefit from a focus on changing the
behaviors of both children and their parents.
The high prevalence of underweight warrants awareness of health care practitioners who – in
the current obesity epidemic – may be more focused on detecting and treating overweight
than underweight. The incessant nature and long-term health consequences of childhood
weight problems [6-10] and the observed high prevalence of under- and overweight among
four-year-old children suggests preventions and interventions targeting unhealthy weights
should start early in life. Longitudinal studies are needed for causal inferences. Yet, it is
tempting to speculate that assessing eating and feeding patterns at a young age – for instance
at child health centers – could help identify children at risk for over- and underweight, as
these behaviors are already highly associated with children‟s BMI by the age of four years.
The effectiveness of such a screening policy should be carefully monitored and this practice
shift should be evaluated in terms of costs and benefits.
BMI, Body mass index; CEBQ, Child Eating Behaviour Questionnaire; CFQ, Child Feeding
Questionnaire; OR, Odds ratio; SD, Standard deviation; 95% CI, 95% confidence interval
The authors declare that they have no competing interests.
PWJ conceptualized the study, performed statistical analyses and drafted the manuscript. SJR
made substantial contributions to the acquisition and interpretation of the data. JDM was also
involved in the interpretation of the data. VWVJ, HR, AH, and FCV made substantial
contributions to the conception and design of the study. VWVJ, AH and FCV also acquired
funding for the study. HT was involved in the conceptualization of the study, the
interpretation of the data and supervised the drafting of the manuscript. All authors critically
revised the manuscript and approved the final version of the manuscript.
The Generation R Study is conducted by the Erasmus MC – University Medical Centre
Rotterdam in close collaboration with the Erasmus University Rotterdam, School of Law and
Faculty of Social Sciences; the Municipal Health Service Rotterdam area, Rotterdam; the
Rotterdam Homecare Foundation, Rotterdam; and the Stichting Trombosedienst &
Artsenlaboratorium Rijnmond (STAR), Rotterdam. We gratefully acknowledge the
contribution of the participating pregnant women and their partners, general practitioners,
hospitals, midwives and pharmacies in Rotterdam.
This work was supported by the Erasmus MC – University Medical Centre Rotterdam,
Erasmus University Rotterdam, and the Netherlands Organization for Health Research and
Development (ZonMW). Additional grants were received from the Netherlands Organization
for Health Research and Development (ZonMW “Geestkracht” program, grant number
10.000.1003), the Netherlands Organization for Scientific Research (NWO – ZonMW, VIDI
grant number 017.106.370 to HT; and NWO - Marie Cofund Action, Rubicon grant number
446-11-010 to PWJ), and the Sophia Foundation for Medical Research SSWO (grant number
602 to PWJ).
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