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R E S E A R C H A R T I C L E Open Access
Physical activity, depressed mood and
pregnancy worries in European obese pregnant
women: results from the DALI study
Linda de Wit
1
, Judith G. M. Jelsma
1
, Mireille N. M. van Poppel
1,2*
, Annick Bogaerts
3
, David Simmons
4
,
Gernot Desoye
5
, Rosa Corcoy
6,7
, Alexandra Kautzky-Willer
8
, Jürgen Harreiter
8
, Andre van Assche
9
,
Roland Devlieger
9
, Dirk Timmerman
9
, David Hill
10
, Peter Damm
11
, Elisabeth R. Mathiesen
11
,
Ewa Wender-Ozegowska
12
, Agnieszka Zawiejska
12
, Pablo Rebollo
13
, Annunziata Lapolla
14
, Maria G. Dalfrà
14
,
Stefano Del Prato
15
, Alessandra Bertolotto
15
, Fidelma Dunne
16
, Dorte M. Jensen
17
, Liselotte Andersen
17
and Frank J. Snoek
18,19
Abstract
Background: The purpose of this study was to examine the association between mental health status (i.e.
depressed mood and pregnancy-related worries) and objectively measured physical activity levels in obese
pregnant women from seven European countries.
Methods: Baseline data from the vitamin D and lifestyle intervention for the prevention of gestational diabetes
mellitus (DALI) study were used. Time spent in moderate-to-vigorous physical activity (MVPA) and sedentary
behaviour was measured with accelerometers. Depressed mood was measured with the WHO well-being index
(WHO-5) and pregnancy-related worries with the Cambridge Worry Scale (CWS). In addition, socio-demographic
characteristics, lifestyle factors, and perceptions and attitude regarding weight management and physical activity
were measured. Linear regression analyses were performed to assess the association of mental health status with
MVPA and sedentary behaviour.
Results: A total of 98 obese pregnant women from Austria, Belgium, Ireland, Italy, Poland, Spain and the Netherlands
were included. Women had a mean age of 31.6 ± 5.8 years, a pre-pregnancy BMI of 34.1 ± 4.3 kg/m
2
, and were on
average 15.4 ± 2.8 weeks pregnant. WHO-5 scores indicative of depressed mood (<50) were reported by 27.1 % of the
women and most frequently endorsed pregnancy-related worries pertained to own and the baby’s health. Women
with good well-being spent 85 % more time in MVPA compared to women with a depressed mood (P=0.03).No
differences in MVPA levels were found for women with no, some, or many pregnancy worries. Depressed mood and
pregnancy-related worries were not associated with sedentary behaviour.
Conclusions: These findings suggest that in pregnant women who are obese, a depressed mood, but not
pregnancy-related worries, may be associated with less physical activity. The combined risk of poor mental health and
low physical activity levels makes women vulnerable for pregnancy complications. Whether a depressed mood may be
a barrier for improving physical activity warrants further study.
Keywords: Exercise, Mental health, Pregnancy, Obesity
* Correspondence: mnm.vanpoppel@vumc.nl
1
Department of Public and Occupational Health, EMGO+ Institute for Health
and Care Research, VU University Medical Centre, Van der Boechorststraat 7,
1081BT Amsterdam, The Netherlands
2
Institute for Sport Science, University of Graz, Graz, Austria
Full list of author information is available at the end of the article
© 2015 de Wit et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://
creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
de Wit et al. BMC Pregnancy and Childbirth (2015) 15:158
DOI 10.1186/s12884-015-0595-z
Background
There is compelling evidence that physical activity during
pregnancy is associated with fewer complications during
pregnancy and delivery, lower chance of gestational dia-
betes (GDM), lower rates of hypertension [1–4], and bet-
ter mental health status [5–8].
The American College of Obstetrics and Gynaecolo-
gists (ACOG) recommends pregnant women to be active
in moderate intensity activities (3–5 metabolic equiva-
lents) for at least 30 min on most, and preferably all,
days of the week [9]. However, adherence to these rec-
ommendations appears to be low, with less than 50 % of
all women meeting the ACOG recommendations pre-
pregnancy and throughout pregnancy in the USA [4, 6,
10] and in the EU [11, 12].
With the growing number of overweight (body mass
index (BMI) > 25 kg/m
2
) and obese (BMI > 30 kg/m
2
)
women of reproductive age [13], obesity during pregnancy
is becoming an increasing problem. Obesity in pregnancy
increases the risk of excessive weight gain, and the risk of
pregnancy-related complications, such as GDM [14]. In
pregnant women who are overweight and obese, physical
activity is of even greater importance, since it can help im-
prove these pregnancy outcomes [4, 15, 16].
A better understanding of the factors related to low
physical activity levels in pregnant women in general is
required in order to maximize acceptability and efficacy
of lifestyle interventions [17, 18]. One predictor of low
physical activity levels that has been well studied outside
of pregnancy is poor emotional well-being signifying de-
pression [19–21]. People with depressive symptoms are
likely to be less physically active [19]. Conversely, in-
creasing physical activity can help to reduce depressive
symptoms in previously inactive people [20]. Also in
pregnancy, research suggests that low levels of phys-
ical activity are associated with poorer mental health
(reviewed in [18]), but the evidence is less convincing.
Studies had either a small sample size [2, 8, 22] or
physical activity was measured with a (non-validated)
diary or questionnaire [23]. Therefore, in this study
we measured physical activity levels objectively in a
larger study sample, in order to provide more accur-
ate assessment of the relationship between physical
activity and mental health.
In pregnant women who are overweight or obese, a
poorer mental health status has been found compared to
non-obese women [24, 25]. Feelings of humiliation and
medicalization of being obese and pregnant appear to
have a negative impact on women’s mental health status
[26]. In addition, stigma towards obese individuals may
lead to a lower self-esteem and may negatively impact
mental health [13, 26, 27]. Pregnancy may be experi-
enced as a distressing period, leading to anxieties. Inse-
curity about the baby’s health, possibility of miscarriage,
and concerns about giving birth are especially reported
in the first trimester [28]. Women who are depressed or
anxious in pregnancy have a higher risk of adverse preg-
nancy or birth outcomes [29, 30].
Similar to other populations, obese pregnant women
with poor mental health (i.e. depressed mood and
pregnancy-related worries) might be less physically active,
which may further increase their risk for adverse preg-
nancy outcomes [18]. Moreover, poor mental health may
limit the effectiveness of physical activity interventions in
obese pregnant women [31]. Therefore, the aim of this
study is to examine the association between mental health
status and objectively measured physical activity levels of
obese pregnant women. For this purpose, we employed
data from the European vitamin D and lifestyle interven-
tion for gestational diabetes mellitus prevention (DALI)
study. This allows insight into the association between
mental health and physical activity in obese pregnant
women throughout Europe.
Methods
Participants
For this study, baseline data from the DALI project
(ISRCTN70595832) were used. Baseline data were col-
lected between October 31, 2011 and April 30, 2013. The
study design and data collection of the DALI project are
described in detail elsewhere [32]. In summary, this pro-
ject aims to identify the best available measures to prevent
GDM in an ongoing pregnancy, and therefore a rando-
mised controlled trial was conducted in nine European
countries: the United Kingdom, Ireland, the Netherlands,
Belgium, Poland, Italy, Spain, Austria, Denmark (2 study
centres), with women from a diverse range of socio-
economic and ethnic backgrounds. For all nine countries,
the study design and procedures were approved by the
Medical Ethics committee of the respective centres
(Cambridge, United Kingdom: National Research Ethics
Service, Norwich Research Ethics Committee; Galway,
Ireland: Clinical Research Ethics Committee, Galway
University Hospitals; Amsterdam, the Netherlands: Ethical
Committee of the VU University Medical Center; Leuven,
Belgium: Commissie Medische Ethiek van de Universitaire
Ziekenhuizen KU Leuven; Poznan, Poland: Komisja
Bioetyczna Przy Uniwersytecie Medycznym im. Karola
Marcinkowskiego W Poznaniu; Padua, Italy: Il Comitato
Etico per la Sperimentazione Clinica della Provincia di
Padova; Barcelona, Spain: Comité Ético de Investigación
ClínicadelaFundaciódeGestióSanitariadelHospitalde
la Santa Creu i Sant Pau; Vienna, Austria: Ethik Kommis-
sion Medizinische Universität Wien;
Copenhagen and Odense, Denmark: De Videnskabsetiske
Komiteer D for Region Hovedstaden). Participating hospi-
tals and surrounding midwife, obstetrician and general
practices were involved in recruitment. Women were
de Wit et al. BMC Pregnancy and Childbirth (2015) 15:158 Page 2 of 10
followed for about 7 months (from 10 weeks of pregnancy
until delivery). Pregnant women were included if aged
18 years and older, were less than 20 weeks pregnant, had a
singleton pregnancy, and had a pre-pregnancy body mass
index (BMI) ≥29 kg/m
2
based on self-reported weight and
measured height. This BMI criterion was agreed upon fol-
lowing a review of local obesity prevalence to ensure all
sites had the potential to recruit sufficient women. In a pilot
study, the lifestyle interventions (diet and/or exercise) and
measurement procedures were tested in each country.
Although women who were diagnosed with GDM at base-
line (using International Association of the Diabetes in
Pregnancy Study Groups (IADPSG) criteria defined as
fasting venous plasma glucose ≥5.1 mmol/l and/or 1 h
glucose ≥10 mmol/l and/or 2 h glucose≥8.5 mmol/l) [33]
were excluded from the DALI intervention study, they
were not excluded for analysis presented in this paper.
Measures
Physical activity
Physical activity was objectively measured with an
Actigraph GT3X, GT1M or Actitrainer accelerometer (all
three devices made by ActiGraph, Pensacola, Florida,
USA). Previous validation studies found physical activity
estimates from the three devices very comparable [34–36].
Although the GT3X is a tri-axial accelerometer, it was
analysed from the vertical plane only to standardize activ-
ity estimates across the three accelerometers. All three ac-
celerometers are lightweight devices with a sampling
frequency of 60–80 (Hz). In this study we used a 1 min
epoch. Accelerations derived from participant’s move-
ments were converted into counts per minute.
Participants were asked to wear the accelerometer
from waking up until going to bed, attached to the right
hip by an elastic waist belt, for at least 3 days. The Acti-
graph accelerometer has previously gained validity and
reliability in free living conditions in adults for between
3 and 5 days [37]. The participants were asked to re-
move the accelerometer while swimming, showering or
bathing. For non-wearing intervals, participants were
instructed to write down in a diary how they spent their
time.
Crude data were obtained using ActiLife 6 (ActiGraph,
LLC, Pensacola, Florida, USA). Periods with no counts
for at least 60 min were defined as non-wear time. Days
with less than 480 min activity were labelled as invalid
data and excluded for analysis [38]. Only women with
data for at least three valid days were included [38].
Using the Freedson cut-off points [39], the number of mi-
nutes per day in light (100–1951 counts/min), moderate
(1952–5724 counts/min) and vigorous (>5724 counts/
min) activity were calculated as well as time spent seden-
tary (<100 counts/min). These cut-off points are widely
used, also in pregnancy [7, 40]. Swimming time, recorded
in the diary, was added to MVPA, based on the Ainsworth
cut-off points [41], a procedure recommended by Esliger
et al. [42]. For analysis, the time spent in moderate-to-
vigorous activity (MVPA) minutes per day) and in seden-
tary behaviour (as proportion of total wear time) were
used.
Mental health
Mental health was assessed based on questionnaire data.
Questionnaires were administered in the main language of
the site: English (UK and Ireland), Dutch (Netherlands
and Belgium), Polish, Italian, Spanish, German (Austria)
and Danish.
The WHO well-being index (WHO-5) was used to as-
sess emotional well-being [43]. This uni-dimensional
questionnaire contains five statements, describing positive
moods (e.g. good spirits, relaxation). Each item was rated
on a 6-point Likert scale, ranging from 0 (‘at no time’)to5
(‘all of the time’) pertaining to the past 2 weeks. Total
scores were calculated and standardized, ranging from 0
to 100. A total score of 50 or above was considered as
good well-being, while a score below 50 indicated de-
pressed mood. This is not a formal depression diagnosis
but signifies likely depression [44]. Cronbach’s alpha was
0.83 for all items. Validated versions of the WHO-5 were
available for all the languages required in the study.
Pregnancy-related worries were measured with the
Cambridge Worry Scale (CWS) [28]. The CWS has good
reliability and validity in pregnant women, and overall a
strong association with trait anxiety [28]. This 13-item
scale assesses current concerns across four domains:
social-medical, socio-economic, health and relationships.
Responses were scored on a 6-point Likert-scale, ranging
from 0 (‘not a worry) to 5 (‘major worry’) for each item.
Total scores (0–70) and domain scores (socio-medical
0–20, socio-economic 0–15, health 0–20 and relationships
0–10) were calculated, with higher scores indicating more
worrying. There is no established clinical cut-off point.
We stratified total scores into tertiles: no or few worries
(score ≤13), some worries (score 14–25) and many wor-
ries (score ≥26). Cronbach’s alpha was 0.86 for all items.
Spearman correlation between WHO-5 and total CWS
was 0.44. The CWS was only available in English and was
translated into all the other languages (without back-
translation).
Other variables
Socio-demographic information was collected at base-
line, including age, country, ethnicity, household com-
position, education (highest completed level) and work
status. In addition, aspects such as parity and lifestyle
factors at baseline, (e.g. smoking (yes/no) and alcohol
consumption (yes/no)) were assessed.
de Wit et al. BMC Pregnancy and Childbirth (2015) 15:158 Page 3 of 10
Pre-pregnancy weight in kilograms divided by height
in squared meters (kg/m
2
) was used to calculate Body
Mass Index (BMI). Pre-pregnancy weight (kg) was based
on self-report, while height was measured at baseline
with a stadiometer (SECA 206). Objective height meas-
urement was obtained with an accuracy to the nearest
centimeter, and the average value of two measurements
was used.
Furthermore, attitude, social support and self-efficacy
outcome expectancies (based on the Health Action
Process Approach (HAPA) model [45] regarding weight
and physical activity management during pregnancy
were measured. Women indicated the extent to which
they agreed with eight items; each item on a 11-point
Likert-scale, ranging from 0 (‘not at all’)to10(‘very
much’). One attitude item pertained to current weight
and one attitude item pertained managing weight. Three
items pertained to self-efficacy beliefs regarding weight
and physical activity management; one item pertained to
social support in physical activity and two items per-
tained to outcome expectancies regarding weight and
physical activity management.
Statistical analysis
For all variables frequencies, means, and standard devia-
tions were calculated. Median values were presented if a
continuous variable was not normally distributed. To
compare distribution of variables in the different mental
health categories (good emotional well-being/depressed
mood and tertiles for pregnancy worries), t-tests and
one-way ANOVAs were performed for normally distrib-
uted variables, non-parametric tests for not-normally
distributed variables, and chi-square tests for dichotom-
ous variables.
To analyze the association between mental health and
objective physical activity, linear regression analyses were
performed for the WHO-5 well-being index (dichoto-
mised) and the Cambridge Worry Scale (in tertiles) com-
bined in the same model. In addition, associations with
the proportion of wear time spent in sedentary behavior
were assessed. To test the (possible) clustering effect
within countries, multilevel analysis with a random inter-
cept were performed. The country of recruitment and the
individuals were the levels in the analyses. Because of the
positively-skewed distribution of MVPA (min/day), a nat-
ural log transformation was executed for the linear regres-
sion analyses. Because of the log transformed dependent
variable in the regression analyses, the exponent of the
beta minus 1 represents the % of change in MVPA be-
tween mental health categories.
Interactions between mental health and age, ethnicity,
prepregnancy BMI, smoking, alcohol consumption, and
parity were assessed, by adding the interaction terms
one by one to the regression model. However, none of
the interaction terms was significant (p< 0.05).
Factors found to be associated with both mental health
and physical activity in previous research were considered
potential confounders (age, ethnicity, occupational status,
household composition, prepregnancy BMI, smoking, alco-
hol consumption, gestational age, parity). All the variables
were entered in the models one by one. Confounding was
defined as a change in the regression coefficient of more
than 10 % [46].
After controlling for confounding, the HAPA factors
(attitude, self-efficacy, social support and outcome expect-
ancy) were added to the models, in order to assess
whether these factors confounded the association between
mental health and MVPA and/or sedentary behavior.
Significance level of the associations in the final model
was set at P-value 0.05. The data were analysed using
SPSS 20.0 (IBM Corporation, Armonk, NY, USA).
Results
A total of 258 women were measured at baseline and
132 of them wore an accelerometer (except in the UK
and Denmark). Of those who wore accelerometers, 14
had no valid data for 3 days and 20 had software prob-
lems. These excluded women (n= 34) had a higher pre-
pregnancy BMI (mean 40.6 kg/m
2
;P< 0.01) and were
further along in their pregnancies (16.8 weeks; P= 0.03).
Finally, 98 women with valid data were included in the
analyses. The mean age was 31.6 ± 5.8 years and most
were white/Caucasian (75.5 %) and had at least a sec-
ondary education (81.6 %) (Table 1). At baseline meas-
urement, women were 15.4 ± 2.8 weeks pregnant. Just
over a quarter (27.1 %) of the total sample (n= 26) had a
depressed mood (WHO-5 score < 50). These women re-
ported a significantly more positive attitude towards
physical activity and scored lower on perceived social
support (P< 0.05) (Table 1). In addition, women with a
depressed mood had more pregnancy-related worries,
both overall and for the specific domains (P< 0.05)
(Table 1).
Physical activity levels are displayed in Table 2. On
average, women wore the accelerometer for almost 13 h
(773.8 min) per day, and were sedentary 62.3 % of that
time. Fifty percent of the women spent fewer than
23 min (inter quartile range 12.3–35.7) in MVPA per
day. Women with a good well-being were involved in
MVPA approximately 24 min per day, while women with
a depressed mood spent about 13 min per day in MVPA
(P< 0.05). The time spent in MVPA did not differ be-
tween women with more pregnancy-related worries
compared to women with less worries (P= 0.74).
Table 3 shows the results of the linear regression analyses
for mental health in association with time spent in MVPA
(minutes/day) and sedentary behaviour (proportion of total
de Wit et al. BMC Pregnancy and Childbirth (2015) 15:158 Page 4 of 10
wear time). In the adjusted model, women with good well-
being spent 70 % more minutes per day in MVPA com-
pared women with a depressed mood (P= 0.04). Adding a
random intercept for country did not (significantly) im-
prove the model, and was therefore not included in the
models. Adding HAPA factors (self-efficacy, attitude
and social support) did not reduce the association be-
tween depressed mood and physical activity. In this
model (model 2), women with good well-being spent
85 % more time in MVPA compared to women with
depressed mood (P= 0.03) (Table 3). Pregnancy-related
worries were not significantly associated with MVPA in
Table 1 Baseline characteristics
Characteristic Total sample Depressed mood
a
Good well-being
a
(n= 98) (n= 26) (n= 70)
Country (n)
Spain 20 5 15
Austria 27 5 22
Belgium 16 7 9
Poland 10 4 6
Italy 1 0 1
Ireland 7 1 6
The Netherlands 17 5 12
Age (mean ± SD) 31.6 ± 5.8 30.6 ± 6.8 32.0 ± 5.5
Pre-pregnancy BMI (mean ± SD) 34.1 ± 4.3 35.0 ± 5.7 33.8 ± 3.7
Weeks of pregnancy (mean ± SD) 15.4 ± 2.8 15.8 ± 2.7 15.4 ± 2.9
Pregnant before (% yes) 54.2 53.8 54.4
Gestational diabetes mellitus (%) 13.5 19.2 11.4
Smoking behaviour (% yes) 10.3 19.2 7.2
Any alcohol consumption (% yes) 6.3 4.0 7.2
Ethnicity (% white/Caucasian) 75.5 61.5* 81.4*
Household composition (% living with partner) 85.3 76.0 88.2
Education (% ≥vocational education) 81.6 84.6 80.0
Occupational status (%)
Home duties 5.2 3.8 5.8
Unemployed/not able to work 17.5 19.2 17.4
Working (fulltime/part-time)/student 77.3 76.9 76.8
Perceptions and attitude
b
(median (IQR))
Attitude to current weight 8.0 (6–9) 8.0 (6–10) 7.0 (6–9)
Attitude to physical activity 9.0 (7–10) 10.0 (8–10)* 8.0 (7–10)*
Self-efficacy 21.0 (17–24.) 21.0 (15–24) 21.0 (17–24)
Social support 8.0 (6–10) 7.0 (5–8)* 8.5 (6–10)*
Outcome expectancy 18.0 (15–20) 18.0 (17–20) 17.0 (14–20)
Cambridge Worry Scale (total 13 items) (median (IQR)) 19.0 (11–28) 28.0 (20–40)** 15.0 (10–25)**
Cambridge Worry Scale dimensions (median (IQR))
Social-medical 5.0 (2–10) 8.5 (4–12)* 4.0 (2–9)*
Socio-economic 4.0 (1–8) 7.5 (2–10)* 4.0 (1–6)*
Health 9.0 (5–12) 13.0 (9–15)** 7.0 (4–10)*
Relationships 0.0 (0–3) 4.0 (0–5)** 0.0 (0–1)**
*P< 0.05; differences between depressed mood and good well-being
** P< 0.001; differences between depressed mood and good well-being
a
Data from WHO-5 were missing for 2 participants
b
Based on the HAPA model
de Wit et al. BMC Pregnancy and Childbirth (2015) 15:158 Page 5 of 10
crude or corrected models (Table 3), and neither as-
pects of mental health were associated with sedentary
behaviour (Table 3).
Discussion
To the best of our knowledge, we are the first to have
studied the associations between emotional well-being
and pregnancy-related worries on the one hand, and phys-
ical activity, and sedentary behavior on the other, in obese
pregnant women across different European countries.
Results show that in obese pregnant women, 27 % had de-
pressed mood and these women were significantly less
involved in MVPA compared to women with a good well-
being. Interestingly, pregnancy-related worries did not
significantly impact MVPA levels.
Thefactthatwemeasuredphysicalactivitywithanac-
celerometer that provides objective information about in-
tensity and duration of different physical activity in daily
life [47] is a strength of the study. Previous studies regard-
ing the association between mental health and MVPA
used physical activity questionnaires or diaries that have a
low correlation with objective physical activity measure-
ment [7, 8]. In addition, these studies were mostly
performed in a normal-weighted pregnant population,
while our study only included women with a higher BMI
who may have worse mental health and lower MVPA
levels [4, 5, 24]. Despite these methodological differences,
our findings corroborate earlier observations suggesting
that a depressed mood is a barrier to be active or to be-
come more active [5, 31].
In our study we operationalized mental health along
two dimensions: emotional well-being (depressed mood)
and pregnancy-related worries, using validated question-
naires. In our population, 27.1 % of the women had a de-
pressed mood, indicating likely depression, which is
somewhat higher than found in Sweden by Claesson and
colleagues, who reported around 18 % depression in
obese women who were 15 weeks pregnant [48]. In a re-
cent meta-analyses, the median prevalence of depressive
symptoms in pregnant women who were obese was
33 %, compared to 22.6 % in normal-weight pregnant
women [25]. Differences in depression prevalence may
be attributed to case-mix or instruments used. For in-
stance, in the study of Claesson et al. [48], fewer women
smoked, more women lived together with a partner, and
depressive symptoms were measured with the Edinburgh
Postnatal Depression Scale [49].
The CWS, used to assess pregnancy-related worries,
was found to be highly correlated with trait anxiety, and
especially the cognitive element [28]. Our study shows
no association with MVPA, suggesting that ‘anxious
thoughts’are not per se (linear) related to physical activ-
ity. This is in line with earlier findings [2, 8]. Anxious
pregnant women may be more restless and nervous,
which may lead to increased activity levels. On the other
hand, women who have high concerns about the baby’s
health and miscarriages may limit their physical activity
purposively [31]. The relationship may indeed be curvi-
linear. Exploring the association between (extreme high
and low) anxiety and physical activity behavior in preg-
nancy may be a fruitful area for future research.
Correction for possible confounders in analyses with
MVPA and mental health led in the first step only to cor-
rection for lifestyle factors (BMI smoking behaviour, alcohol
consumption). Remarkably, no interference with socio-
economic factors was found, while previous studies have
identified these as important predictors of both mental
health and exercise behaviour [7, 17, 50, 51]. A possible ex-
planationforourdifferentresultmaybethatoursample
was relatively well-educated and employed (81.6 % with at
Table 2 Physical activity levels for total sample and stratified for the different categories of the WHO-5 well-being index and
Cambridge Worry Scale
Total WHO-5 well-being index Cambridge worry scale
Depressed
mood
Good well-being Many worries Some worries No or few
worries
Minutes of wear
time per day
mean (SD) 773.8 (91.1) 771.5 (92.6) 772.2 (91.0) 775.9 (92.7) 775.1 (93.2) 759.7 (83.7)
MVPA
a
minutes per day median (IQR) 23.1 (12.3–35.7) 13.3* (8.6–30.0) 24.4* (13.1–38.4) 21.3 (10.8–30.3) 24.0 (12.2–40.8) 24.3 (14.1–35.1)
Proportion of total
wear time (%)
3.4 (2.8) 2.4* (2.1) 3.6* (2.8) 2.9 (1.9) 3.6 (3.1) 3.6 (3.0)
Sedentary behaviour
b
minutes per day
mean (SD) 484.2 (22.3) 506.2 (96.2) 479.0 (81.1) 477.0 (79.7) 495.3 (95.3) 485.8 (86.1)
Proportion of total
wear time (%)
62.3 (9.7) 65.1 (11.2) 61.7 (8.6) 61.5 (10.0) 63.3 (9.6) 63.4 (9.0)
*P< 0.05; differences between depressed mood and good well-being
a
Moderate-to-vigorous activity (≥1952 counts per minute)
b
< 100 counts per minute
de Wit et al. BMC Pregnancy and Childbirth (2015) 15:158 Page 6 of 10
least vocational education and 77.3 % had work) and were
interested in participating in a lifestyle intervention study.
In a second step, all HAPA factors were added to the
models. Although these factors led to some change in the
effect estimate, this did not reduce the strength of the as-
sociations. The measured perceptions and attitudes,
although interesting in their own right, did not explain the
association between mental health and physical activity.
In our analyses we did not find a clustering effect between
the European countries in the association. This may imply an
Europe-wide homogeneity of the associations in obese
pregnant women with different cultural background. An ex-
planation for this finding is that included countries, albeit with
different cultures, were all Western societies with highly simi-
lar attitudes towards weight and physical activity in pregnancy
[13, 26]. Future studies in a more culturally heterogeneous
sample may shed light on the issue of perceptions and stigmas
around weight gain, physical activity and obesity in pregnancy.
Some limitations of our study should be acknowledged.
We included women who consented to take part in the
DALI study and are therefore likely to be motivated to
change their physical activity behaviour compared to
Table 3 Linear regression analyses examining the relationship of mental health with moderate-to-vigorous activity (MVPA) (minutes/
day) and sedentary behaviour (% of wear time)
Ln(MVPA) Ratio 95 % CI p-value
Crude model
Good well-being vs depressed mood 1.72 0.99 –2.99 0.06
Many worries (ref) 1.00
Some worries 1.27 0.72 –2.23 0.40
No or few worries 1.18 0.64 –2.19 0.59
Model 1
Good well-being vs depressed mood 1.70 1.02 –2.82 0.04
Many worries (ref) 1.00
Some worries 0.97 0.58 –1.62 0.89
No or few worries 0.92 0.52 –1.61 0.77
Model 2
Good well-being vs depressed mood 1.85 1.06 –3.24 0.03
Many worries (ref) 1.00
Some worries 0.94 0.55 –1.61 0.83
No or few worries 1.01 0.57 –1.80 0.97
Sedentary behaviour Difference 95 % CI p-value
Crude model
Good well-being vs depressed mood −16.82 −60.76 –27.13 0.45
Many worries (ref) 0
Some worries 8.05 −35.78 –51.89 0.72
No or few worries −18.62 −66.52 –29.27 0.44
Model 1
Good well-being vs depressed mood −18.94 −63.95 –26.08 0.41
Many worries (ref) 0
Some worries 4.88 −40.01 –49.76 0.83
No or few worries −16.17 −64.86 –32.51 0.51
Model 2
Good well-being vs depressed mood −36.24 −85.07 –12.60 0.14
Many worries (ref) 0
Some worries 1.70 −43.34 –46.74 0.94
No or few worries −13.43 −62.25 –35.39 0.59
Model 1: Corrected for BMI, smoking behaviour, and alcohol consumption
Model 2: Corrected for BMI, smoking behaviour, alcohol consumption, attitude weight, attitude physical activity, self-efficacy, social support and outcome expectancies
Bold font indicates statistically significant associations (p< 0.05).
de Wit et al. BMC Pregnancy and Childbirth (2015) 15:158 Page 7 of 10
women who declined to participate. Selection bias may
have led to an underestimation of the studied associations.
The use of accelerometer in (obese) pregnant women
has been subject of discussion [52, 53]. Due to higher
waist circumference and the abdominal shape of obese
pregnant women, the accelerometer may change position
and measurement may be less accurate. Nevertheless,
measuring MVPA by accelerometry may be the best
choice in an intervention that promotes physical activity
in obese pregnant women [52]. In addition, the Freedson
cut-off points were used to determine different activity
levels. It is arguable if these cut-off points are adequate in
our obese pregnant women, because no golden standard
is available and optimal cut-off points may vary across
populations [7, 52]. Another concern in our study was that
there were some women (n=34) with not enough valid
data or software problems. Additional limitations are that
no data on prepregnancy physical activity or mental health
were available, no data on pregnancy-related symptoms
such as nausea, and that prepregnancy BMI was based on
self-reported data. Furthermore, the study had a relative
small sample size, and was imbalanced, in addition, with
only 26 women with depressed mood.
Of course we need to be cautious in interpreting our
data, as they are cross-sectional and we cannot exclude re-
versed causality. Low levels of physical activity may induce
or maintain depressed mood and increase pregnancy-
related worries. Future studies should aim to assess the
association between mental health status and MVPA lon-
gitudinally and determine the causal relationship. Because
worries and emotional well-being may vary over time, and
physical activity levels may decrease with progressing
pregnancy, associations may also change.
Conclusion
Although women with good well-being spent significantly
more minutes in MVPA than those who with a depressed
mood, still in our sample only 29.6 % of the women com-
plied with the recommendations of MVPA for least 30 min
per day. There is ample room for improvement in the total
population of pregnant women who are obese. This is
exactly the purpose of the DALI study, where pregnant
women are offered lifestyle counselling based on principles
of motivational interviewing [32].
However, for pregnant women who are obese and have
a depressed mood there is a stronger need for improving
physical activity behaviour. The combined risk of having
poor mental health, obesity and low physical activity levels
makes this group extra vulnerable for pregnancy compli-
cations. The short WHO-5 might be a suitable instrument
for screening in clinical practice. Whether a lifestyle
intervention is similarly effective in women with good
well-being and those with a depressed mood remains to
be seen. Possibly, poor mental health is a barrier for
improving lifestyle. Therefore, longitudinal analyses of the
association of mental health and changes in physical
activity after lifestyle intervention are warranted. However,
based on our findings there is a need for focused efforts
for the promotion of physical activity among obese
pregnant women with at-risk levels of depressive mood.
Competing interest
The authors declare that they have no competing interests.
Authors’contributions
JJ contributed to the analysis of the questionnaire and writing of the
manuscript and took the lead in redrafting the script following editorial
review. DS contributed to the data collection in the UK. RC and JA
contributed to the data collection in Spain. JH and AK contributed to the
data collection in Austria. AA, RD, DT contributed to the data collection in
Belgium. PD and EM contributed to the data collection in Denmark. EWO
and AZ contributed to the data collection in Poland. AL, MDG, SP, AB
contributed to the data collection in Italy. FD contributed to the data
collection in Ireland. AB, FS and MvP contributed to the conception and
design of the study and reviewed the manuscript. DS, GD, RC, AK, DH, EM,
PD, PR, AL, FD, DJ and LA have made substantial revisions to the draft
manuscript. All of the authors have read and approved the final manuscript.
Acknowledgments
We are deeply grateful to the participants who participated in this study.
Financial support
The research leading to these results has received funding from the
European Community’s 7th Framework Programme (FP7/2007-2013) under
Grant Agreement no 242187 and from The Netherlands Organization for
Health Research and Development (ZonMw), grant number:200310013.
Author details
1
Department of Public and Occupational Health, EMGO+ Institute for Health
and Care Research, VU University Medical Centre, Van der Boechorststraat 7,
1081BT Amsterdam, The Netherlands.
2
Institute for Sport Science, University
of Graz, Graz, Austria.
3
Department of Healthcare Research, PHL University
College, Limburg Catholic University College, Hasselt, Belgium.
4
Institute of
Metabolic Science, Addenbrookes Hospital, Cambridge, UK.
5
Department of
Obstetrics and Gynecology, Medizinische Universität Graz, Graz, Austria.
6
Institut de Recerca de L’Hospital de la Santa Creu i Sant Pau, Barcelona,
Spain.
7
CIBER Bioengineering, Biomaterials and Nanotechnology, Instituto de
Salud Carlos III, Madrid, Spain.
8
Medical University of Vienna, Vienna City,
Austria.
9
KU Leuven Department of Development and Regeneration: Pregnancy,
Fetus and Neonate, Gynaecology and Obstetrics, University Hospitals Leuven,
Leuven, Belgium.
10
Recherche en Santé Lawson SA, Bronschhofen, Switzerland.
11
University Hospital of Copenhagen - Rigshospitalet, Copenhagen, Denmark.
12
Akademia Medyczna im Karola Marcinkowskiego, Poznan, Poland.
13
BAP Health
Outcomes Research SL, Oviedo, Spain.
14
Universita Degli Studi di Padova, Padova,
Italy.
15
Università di Pisa, Pisa, Italy.
16
National University of Ireland, Galway,
Ireland.
17
Odense University Hospital, Odense, Denmark.
18
Department of
Medical Psychology, EMGO+ Institute for Health and Care Research, VU University
Medical Centre, Amsterdam, The Netherlands.
19
Department of Medical
Psychology,AcademicMedicalCentre,Amsterdam,TheNetherlands.
Received: 10 November 2014 Accepted: 17 July 2015
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