Does health differ between participants and non-participants in the MRI-HUNT study, a population based neuroimaging study? The Nord-Trøndelag health studies 1984-2009.

Abstract

Bias with regard to participation in epidemiological studies can have a large impact on the generalizability of results. Our aim was to investigate the direction and magnitude of potential bias by comparing health-related factors among participants and non-participants in a MRI-study based on HUNT, a large Norwegian health survey.
Of 14,033 individuals aged 50-65, who had participated in all three large public health surveys within the Norwegian county of Nord-Trøndelag (HUNT 1, 2 and 3), 1,560 who lived within 45 minutes of travel from the city of Levanger were invited to a MRI study (MRI-HUNT). The sample of participants in MRI-HUNT (n = 1,006) were compared with those who were invited but did not participate (n = 554) and with those who were eligible but not invited (n = 12,473), using univariate analyses and logistic regression analyses adjusting for age and education level.
Self-reported health did not differ between the three groups, but participants had a higher education level and were somewhat younger than the two other groups. In the adjusted multivariate analyses, obesity was consistently less prevalent among participants. Significant differences in blood pressure and cholesterol were also found.
This is the first large population-based study comparing participants and non-participants in an MRI study with regard to general health. The groups were not widely different, but participants had a higher level of education, and were less likely to be obese and have hypertension, and were slightly younger than non-participants. The observed differences between participants and non-invited individuals are probably partly explained by the inclusion criterion that participants had to live within 45 minutes of transport to where the MRI examination took place. One will expect that the participants have somewhat less brain morphological changes related to cardiovascular risk factors than the general population. Such consequences underline the crucial importance of evaluation of non-participants in MRI studies.

Full text

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RESEARCH ARTICLEOpen Access
Does health differ between participants and non-
participants in the MRI-HUNT study, a population
based neuroimaging study? The Nord-Trøndelag
health studies 1984–2009
Lasse-Marius Honningsvåg1*, Mattias Linde1,2, Asta Håberg1, Lars Jacob Stovner1,2and Knut Hagen1,2
Abstract
Background: Bias with regard to participation in epidemiological studies can have a large impact on the
generalizability of results. Our aim was to investigate the direction and magnitude of potential bias by comparing
health-related factors among participants and non-participants in a MRI-study based on HUNT, a large Norwegian
health survey.
Methods: Of 14,033 individuals aged 50–65, who had participated in all three large public health surveys within the
Norwegian county of Nord-Trøndelag (HUNT 1, 2 and 3), 1,560 who lived within 45 minutes of travel from the city
of Levanger were invited to a MRI study (MRI-HUNT). The sample of participants in MRI-HUNT (n=1,006) were
compared with those who were invited but did not participate (n=554) and with those who were eligible but not
invited (n=12,473), using univariate analyses and logistic regression analyses adjusting for age and education level.
Results: Self-reported health did not differ between the three groups, but participants had a higher education level
and were somewhat younger than the two other groups. In the adjusted multivariate analyses, obesity was
consistently less prevalent among participants. Significant differences in blood pressure and cholesterol were also
found.
Conclusion: This is the first large population-based study comparing participants and non-participants in an MRI
study with regard to general health. The groups were not widely different, but participants had a higher level of
education, and were less likely to be obese and have hypertension, and were slightly younger than non-
participants. The observed differences between participants and non-invited individuals are probably partly
explained by the inclusion criterion that participants had to live within 45 minutes of transport to where the MRI
examination took place. One will expect that the participants have somewhat less brain morphological changes
related to cardiovascular risk factors than the general population. Such consequences underline the crucial
importance of evaluation of non-participants in MRI studies.
Keywords: General population study, Population characteristics, Participation rates, Cardiovascular disease, BMI,
Cholesterol, Education, Neuroimaging, Magnetic resonance imaging
* Correspondence: lassemar@stud.ntnu.no
1Department of Neuroscience, Norwegian University of Science and
Technology, Trondheim 7491, Norway
Full list of author information is available at the end of the article
© 2012 Honningsvåg et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the
Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is properly cited.
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Background
In recent years, participation rates in epidemiological
studies have been declining [1]. However, very few
population-based and clinical studies have extensive
health-related information regarding non-participants. A
systematic review of 116 articles published in 2009 in a
specified epidemiological journal showed that demo-
graphic analyses on participants versus non-participants
were performed in only 10% [2]. However, such data are
of major importance because validity and generalizability
of findings are limited if participants differ substantially
from non-participants. Indeed, several earlier epidemio-
logical studies have found that non-participants tend to
have lower health status than participants [3-5].
The Nord-Trøndelag Health Study (HUNT) is a large
scale epidemiological study conducted in three waves in
the period 1984 to 2008, and included evaluation of
non-participants [6-9]. Magnetic resonance imaging of
the brain was one of many sub-studies integrated into
the last of these (MRI HUNT). The aim of the present
study is to compare the health related factors collected
in the period 1984 to 2008 between participants and
non-participants in MRI HUNT, which can aid in the in-
terpretation of future reports based on MRI HUNT. To
the best of our knowledge, extensive description of non-
participants in a population-based MRI study has not
been done earlier.
Methods
The HUNT studies were conducted during 1984 to 1986
(HUNT 1), 1995 to 1997 (HUNT 2) and 2006 to 2008
(HUNT3) in the Norwegian county of Nord-Trøndelag,
which is one of 19 counties in Norway, and fairly repre-
sentative of the rest of the country. In all three surveys,
the entire population aged 20 years or older was invited
to participate. The first questionnaire (Q1) was enclosed
with the invitation letter. All were invited to a brief clin-
ical consultation including measurement of blood pres-
sure (BP), height and weight. In HUNT 2 and 3, blood
samples were also acquired. Not all participants took
part in all elements of the health examination, answered
all the questions or filled out additional questionnaires.
In all three HUNT-studies, women were more likely to
attend, and the participation was highest in the age
group 50–79, with lower participation for those older
and younger [10].
In HUNT 1, the main topics were hypertension, dia-
betes mellitus, lung diseases and health-related quality
of life [11]. Of 85,100 eligible individuals, 74,977 (88%)
answered Q1 and also participated in the medical exam-
ination. Previously published studies about the HUNT 1
population has shown that the main reasons for not
attending were that they were busy, lacked interest, had
moved or had health problems [6], and that, among the
elderly, non-participants had poorer health than partici-
pants [12].
HUNT 2 was a more comprehensive study, covering a
wide range of topics, described elsewhere [7].The Q1
included several demographic variables, such as marital
status, education, working status, exercise, use of tobacco,
alcohol, and caffeine, and anxiety and depression. Out of
92,936 invited individuals, 66,140 (71%) participated. A
study of a random sample of non-participants, showed
that the main reasons for non-participation in the age
group 20–69 were lack of time, having moved out of the
county, being too busy at work, having forgotten the invi-
tation, or no particular reason, whereas among those ≥70
many did not feel the need to attend the health survey [7].
Of the participants in HUNT 2, 47,286 had also partici-
pated in HUNT 1.
Apart from a few minor modifications (adding or re-
moving certain items), HUNT 3 is equivalent to HUNT
2 concerning the health-related topics. Of 94,194 invited
adults, a total of 50,839 (54%) answered the Q1 and
attended the medical examination. A participation study
showed that those who were employed, earned a high
salary, had a higher level of education or lived in an in-
land area were more likely to participate [13]. Overall, a
total of 27,980 subjects have participated in all three
HUNT-studies.
MRI-HUNT study (performed 2007–2009)
The cohort invited to participate in the MRI-HUNT
study was drawn from the population who had partici-
pated in HUNT 1, 2 and 3 and was between 50 and
65 years at the time of the MRI acquisition (n=14,033).
The exclusion criteria were limited to MRI contraindica-
tions; pacemaker of the heart, clipped cerebral aneurysm,
cochlear implants, severe claustrophobia or weight above
150 kg. Furthermore, individuals were only included if
their travelling distance to the location of the MRI exam-
ination at Levanger hospital did not exceed 45 minutes.
The aim was to achieve 1000 participants. To attain this,
1,560 individuals who fulfilled these criteria were selected
for potential participation. Those aged 50–65 years who
had participated in HUNT 1, 2 and 3, but were not
invited, were defined as non-invited (MRI-ni) (n=12,473).
MRI contrast agents were not used, and the invitation let-
ter informed that the session would last approximately 30
minutes.
A selective invitation was made in order to obtain the
desired sex and age distribution within the group. Be-
cause of this stratification process, 66 of the 1,560 per-
sons fulfilling inclusion criteria were not invited to the
examination, leaving 1,494 who were invited to attend
the study. 1,088 (73%) of these invited individuals gave
informed consent and 1,006 (476 males and 530 females)
(67% of invited) had successful MRI examinations and
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were defined as MRI participants (MRI-p). A total of
488 persons were invited, but did not participate, mostly
because they declined the invitation or did not answer
(n=406). Other reasons for not participating were that
the scanning was terminated due to claustrophobia
(n=16), muscle cramps (n=5) or the image acquisition
was unsuccessful due to metallic artifacts (n=3). Some
also cancelled the session prior to the scanning (n=28),
did not show up (n=5), had contraindications (n=4),
moved (n=1), died (n=1), were above 65 years (n=1)
or were hospitalized (n=1). Data collection was closed
when the number of participants had passed 1,000, and
the planned scanning of 17 individuals was consequently
cancelled.
Even though the actual number of individuals that were
invited but did not participate was 488, the de-identified
data file we received from HUNT research center
included the 66 persons who were excluded due to stratifi-
cation. Thus, this group of MRI non-participants (MRI-
np) consisted of a total of 554 persons. The numerous rea-
sons for non-participation and ineligibility are summar-
ized in a flowchart (Figure 1).
Variables
For the purpose of this article, divorce and separation
were recoded into the same marital status category. In
HUNT 1 and 2, education (originally five levels) was
categorized in two levels (≤ 12 years or >12 years). In
HUNT 3, education level was measured using infor-
mation from HUNT 2. As to employment status, the
question differed slightly in the three HUNT studies.
In order to enable meaningful comparisons between
them, we differentiated only between employed and
non-employed.
Based on measurement at the medical examinations
in HUNT 1, 2 and 3, the proportion of obese (BMI
>30 kg/m2) was calculated, and systolic and diastolic
BP was registered. In HUNT 2 and 3 blood samples
Stratification exclusions
(n=66/4.2%)
Fulfilling the
inclusion criteria
(n=1,560)
Invited
(n=1,494/95.8%)
Gave consent
(n=1,088/69.7%)
Participants
(MRI-p)
(n=1,006/64.5%)
Scanning terminated or
image not useable
(n=24/1.5%)
No answer or declined to
participate (n=406/26.0%)
Participated in
HUNT 1, 2 and 3
and 50-65 years of
age (n=14,033)
Non-invited (MRI-ni)
(n=12,473)
Non-participants
(MRI-np) (n=554/35.5%)
Other reasons for not
doing the examination
(n=41/2.6%)
Examination cancelled by
researchers
(n=17/1.1%)
Figure 1 Flowchart describing the cohort.
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were analyzed for HDL-cholesterol, total cholesterol,
non-fasting glucose, and triglycerides.
Subjective health was in the three HUNT surveys
assessed with the question “How is your health at the
moment?”, and the four response categories ranging
from “poor” to “very good”, was merged to two. HUNT
2 and 3 contained identical screening questions on head-
ache (“Have you suffered from headache during the last
12 months?”) and chronic musculoskeletal complaints
(Have you suffered from pain or stiffness in muscle and
joints lasting for at least 3 months during the last
year?”). HUNT 2 and 3 had a series of questions regarding
mental health which constituted the Hospital Anxiety and
Depression Scale (HADS).
HUNT 1, 2 and 3 included quite similar, but not
identical, questions regarding alcohol, physical activity
and smoking habits. In order to enable meaningful
comparisons between the surveys, individuals were
divided into two groups with regard to use of alcohol
(abstainers versus non-abstainers), physical activity (active
versus inactive), and smoking (current smokers versus
others).
There were very few missing data on demographical
variables and measured data. No imputation was done
for missing data on measured variables. The questions
which we based two of our variables on (non-employ-
ment in HUNT 2 and daily smoking in HUNT 3) were
asked in such a manner that missing data most sensibly
was interpreted as a negative answer.
Ethics
The Norwegian Data Inspectorate, the Norwegian Board
of Health, and the Regional Committee for ethics in
Medical Research had approved all HUNT studies, in-
cluding MRI-HUNT, and the regional committee also
approved the present analysis. All participants in HUNT
1, 2, 3 and MRI-HUNT gave their informed, written
consent.
Statistical methods
Differences between MRI-p, MRI-np and MRI-ni were
analyzed using data from all three HUNT-studies and
men and women were analyzed separately. In the uni-
variate analyses, Chi-squared test was used for categor-
ical data, and one-way ANOVA for continuous data. If
a Bonferroni-adjusted p-value <0.001 (0.05/50) was
achieved, multivariate analyses were performed for
both sexes in all three HUNT-studies, using logistic
regression with odds ratio (OR) and 95% confidence
intervals (CI), adjusting for age (continuous variable),
and education level (five categories). Total cholesterol,
HDL-cholesterol, non-fasting glucose, HADS-A (Anxiety)
and –D (Depression) were dichotomized using 75-
percentile as cutoff. Additionally, in order to examine how
Table 1 HUNT 1: Characteristics of participants in the MRI study (MRI-p), non-participants (MRI-np) and non-invited
(MRI-ni)
VARIABLESWOMEN MEN
MRI-p
(n=530)
MRI-np
(n=286)
MRI-ni
(n=6678)
pMRI-p
(n=476)
MRI-np
(n=268)
MRI-ni
(n=5695)
p
Demographic
Age (mean [SD])35.1 [4.2]35.1 [4.3] 35.6 [4.5]0.0071
<0.0012
0.722
0.032
35.3 [4.1]35.2 [4.2]35.7 [4.5]0.071
<0.0012
0.432
0.282
Education >12 years (n [%])124 [27.3] 58 [24.2]779 [13.9]117 [28.1] 57 [27.3] 882 [18.6]
Separated or divorced (n [%])24 [4.5]10 [3.5] 303 [4.5]10 [2.1]5 [1.9]161 [2.8]
Non-employed (n [%])16 [3.0]8 [2.8] 339 [5.0]13 [2.7]5 [1.9]196 [3.4]
Health-related
Fair or poor health (n [%])64 [12.1]28 [9.8]834 [12.3]0.452
0.252
0.252
0.652
<0.0011
<0.0012
43 [9.1] 28 [10.5]619 [10.9]0.462
0.562
0.082
0.732
0.1281
0.0042
Physical inactivity (n [%])23 [5.0]14 [5.7]387 [6.8)] 31 [7.2]16 [7.5]412 [8.6]
Daily smoking (n [%])159 [34.3] 84 [34.1]2108 [37.4] 119 [27.7]74 [34.7] 1574 [32.7]
Alcohol abstainers(n [%]) 29 [6.3]19 [7.8]29 [6.3]13 [3.0] 9 [4.2]163 [3.4]
BMI (mean [SD])
BMI ≥30 kg/m2(n [%])
22.6 [2.7]23.5 [3.3] 23.4 [3.4]24.6 [2.3] 24.9 [2.9]24.8 [2.8]
8 [1.5]19 [6.6]339 [5.1] 9 [1.9]18 [6.7]267 [4.7]
Laboratory measurements
SBP (mean [SD])119.3 [13.0]121.0 [12.5]121.0 [13.4] 0.0191
0.132
0.0031
0.0132
129.1 [12.6]129.9 [12.8]130.6 [12.8] 0.0521
0.142
0.0031
0.0332
SBP ≥140 mmHg (n [%])34 [6.4] 24 [8.4]603 [9.0]93 [19.5] 52 [19.4] 1276 [22.7]
DBP (mean [SD])78.6 [8.7]79.7 [9.3]77.9 [9.6]83.8 [8.6] 84.2 [9.9] 82.7 [9.3]
DBP ≥90 mmHg (n [%])55 [10.4] 48 [16.8]759 [11.3] 119 [25.0]76 [28.4] 1253 [22.3]
1. One-way analysis-of-variance 2. Chi-squared test.
BMI: Body mass index; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; Fair or poor health: Fair or poor self-perceived health.
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robust the findings were, the multivariate analyses were
repeated including only individuals weighing <120 kg.
Data analysis was performed with the Predictive Analytic
SoftWare (PASW) Statistics v17.0 by SPSS Inc., IBM
Company (Chicago, IL, USA).
Results
Unadjusted analyses evaluating differences between
MRI-p, MRI-np, and MRI-ni for HUNT 1, 2 and 3 are
shown in Tables 1, 2 and 3. Participants were slightly
younger and a larger proportion had higher level of edu-
cation compared to the two other groups. Consequently,
adjustments for these two factors were performed in the
multivariate analyses.
In univariate analyses, no differences were found for
self-reported health. The most consistent differences be-
tween the groups were found for BP and BMI. In all
three HUNT studies, participants were less likely to be
obese than the two other groups, and in the second
study, participants had lower mean systolic BP. Signifi-
cant but less consistent differences were also found for
cholesterol, HADS-D and employment status. These
variables were therefore examined further with multi-
variate analyses.
In the multivariate analyses, adjusting for differences in
age and education level, obesity were less common among
participants in all studies, most evident in HUNT 1
(Table 4). Excluding those weighing >120 kg did not
Table 2 HUNT 2: Characteristics of participants in the MRI study (MRI-p), non-participants (MRI-np) and non-invited
(MRI-ni)
VARIABLESWOMEN MEN
MRI-p
(n=530)
MRI-np
(n=286)
MRI-ni
(n=6678)
pMRI-p
(n=476)
MRI-np
(n=268)
MRI-ni
(n=5695)
p
Demographic
Age (mean [SD]) 45.7 [4.3]45.8 [4.3]47.1 [4.5]<0.0011
<0.0012
46.0 [4.2]45.9 [4.2]47.2 [4.5] <0.0011
<0.0012
0.0552
0.4632
Education >12 years (n [%])179 [34.0]94 [33.2]1349 [20.1] 156 [32.9]79 [29.8]1292 [22.9]
Separated or divorced (n [%]) 72 [13.6]29 [10.1]713 [10.5] 0.083
0.6592
41 [8.6] 32 [11.9]449 [7.9]
Non-employed (n [%]) 14 [2.6]8 [2.8]220 [3.2]7 [1.5]7 [2.6]131 [2.3]
Health-related
Fair or poor health (n [%])105 [19.8]60 [21.1]1607 [23.9] 0.0632
84 [17.8]36 [13.5]1062 [18.8]0.0872
Physical inactivity (n [%]) 18 [3.8]11 [4.3] 308[5.0]0.361
0.2162
0.4262
<0.0011
<0.0012
0.1622
0.1592
0.0301
<0.0011
0.0172
22 [5.4]14 [6.2]389 [7.8]0.151
0.2882
0.4982
0.0381
0.0042
0.8832
0.4442
0.0611
0.0261
0.0522
Daily smoking (n [%])159 [32.6]88 [33.6]2321 [36.1]
119 [26.9]82 [32.5]1568 [28.7]
Alcohol abstainers(n [%])38 [7.3] 28 [9.9]548 [8.2]19 [4.0]15 [5.8]290 [5.2]
BMI (mean [SD])
BMI ≥30 kg/m2(n [%])
25.1 [3.4]26.3 [4.3] 26.0 [4.2]26.3 [2.7]26.7 [3.4]26.7 [3.2]
46 [8.7] 47 [16.4]1039 [15.4] 44 [9.3]43 [16.0]827 [14.6]
Headache(n [%])274 [58.9] 130 [53.9]3167 [54.4]156 [36.4]73 [34.6] 1644 [35.4]
Musculoskeletal pain(n [%])281 [53.4]137 [48.2] 3654 [54]222 [46.8]113 [42.3] 2618 [46.1]
HADS A score(mean [SD]) 4.2 [3.4]4.6 [3.5]4.6 [3.4]3.7 [2.9] 3.8 [2.8] 4.0 [3.1]
HADS D score(mean [SD])2.9 [2.8]2.9 [2.9]3.4 [2.9]3.5 [2.9]3.3 [2.6]3.7 [3.0]
Antihypertensive use (n [%])14 [2.6]13 [4.5] 370 [5.5]17 [3.6] 9 [3.4]321 [5.6]
Laboratory measurements
SBP (mean [SD])126.1 [15.6] 128.1 [16.6]130.2 [17.7]<0.0011
<0.0012
0.0221
0.2482
<0.0011
0.0082
0.0481
0.0081
0.0051
0.0132
133.2 [13.0] 135.1 [15.3] 135.9 [15.1]0.0011
0.0022
0.0341
0.0412
0.0011
0.0082
<0.0011
0.8311
0.5581
0.7832
SBP ≥140 mmHg (n [%]) 83 [15.7]71 [24.8]1760 [26.0]134 [28.2]89 [33.3] 2046 [36.0]
DBP (mean [SD])77.6 [10.0]78.7 [10.6]78.9 [10.7]82.0 [9.1] 83.6 [10.7]83.3 [10.2]
DBP ≥90 mmHg (n [%])67 [12.6]43 [15.0]1038 [15.3]94 [19.8] 64 [24.0]1417 [25.0]
Cholesterol (mean [SD])5.6 [1.0]5.6 [1.0]5.8 [1.1]5.9 [1.0]5.8 [1.1]6.0 [1.1]
High cholesterol (n [%]) 99 [18.7]52 [18.2]1578 [23.3]122 [25.7]59 [22.1]1682 [29.6]
HDL Cholesterol(mean [SD])1.5 [0.4]1.5 [0.4] 1.5 [0.4]1.2 [0.3]1.2 [0.3] 1.3 [0.3]
Triglycerides (mean [SD])1.3 [0.8]1.4 [0.8] 1.4 [0.9]2.1 [1.2]2.1 [1.3]2.1 [1.3]
Glucose (mean [SD])5.1 [0.8]5.3 [1.6]5.2 [0.9]5.4 [1.2]5.4 [1.1]5.4 [1.3]
Glucose ≥5.6 mmol/l (n [%])106 [20.0]74 [25.9]1742 [25.8]146 [30.7] 83 [31.1]1824 [32.1]
1. One-way analysis-of-variance 2. Chi-squared test.
BMI: Body mass index; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; Fair or poor health: Fair or poor self-perceived health; Antihypertensive use:
Current use of antihypertensive medication; Glucose: Non-fasting glucose; High Cholesterol: Cholesterol ≥6.6 mmol/l.
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change the results (data not shown). Regarding BP, the
most consistent findings were among women, in whom
systolic BP ≥140 mm Hg was less common among MRI-p
than among the two other groups in HUNT 2 and 3.
Among men, these differences were only found between
MRI-p and MRI-ni in HUNT 2. Also among men in
HUNT 2, HDL-cholesterol ≥1.6 was less common among
MRI-p than among MRI-ni. Furthermore, cholesterol >6.5
and HDL-cholesterol >1.7 were less common among
MRI-p compared to MRI-ni in HUNT 3. Regarding em-
ployment status and HADS, the picture was less clear.
Among women in HUNT 3, HADS-D score was lower for
MRI-p compared to MRI-ni and a smaller proportion of
MRI-p was unemployed compared to MRI-np.
Discussion
To the best of our knowledge this paper is the first ex-
tensive description of non-participants in a population-
based MRI study. The present study demonstrate that
participants volunteering and successfully completing
MRI scanning were not widely different from those who
did not participate, and self-reported health did not dif-
fer between them. Notably, however, participants were
less often obese, had a higher level of education, and
were somewhat younger than MRI-np and MRI-ni. Risk
factors for cardiovascular disease (high BP and choles-
terol) were less prevalent among participants. The parti-
cipants were also more likely to be employed. Additionally,
HADS-score was found to be lower among participants,
Table 3 HUNT 3: Characteristics of participants in the MRI study (MRI-p), non-participants (MRI-np) and non-invited
(MRI-ni)
VARIABLES WOMENMEN
MRI-p
(n=530)
MRI-np
(n=286)
MRI-ni
(n=6678)
p MRI-p
(n=476)
MRI-np
(n=268)
MRI-ni
(n=5695)
p
Demographic
Age (mean [SD])57.6 [4.2]57.6 [4.3]58.2 [4.5] <0.0012
<0.0012
0.0852
<0.0012
57.9 [4.1]57.7 [4.2]58.3 [4.5]0.0271
<0.0012
0.0712
0.0012
Education >12 years (n [%])179 [34.0]94 [33.2]1349 [20.1] 156 [32.9]79 [29.8]1292 [22.9]
Separated or divorced (n [%])86 [16.2] 42 [14.7]881 [13.0]56 [11.8] 41 [15.3]619 [10.6]
Non-employed (n [%])101 [19.3]79 [27.9] 1889 [28.1] 76 [16.0]42 [15.7] 1233 [21.7]
Health-related
Fair or poor health (n [%])164 [31.7]100 [35.8] 2097 [32.2]0.4182
0.4732
0.0012
0.5792
<0.0011
0.0222
0.1552
0.7182
0.1581
0.0021
0.0052
110 [23.4]70 [26.6] 1459 [26.3]0.3892
0.4072
0.0582
0.8732
0.0031
0.0302
0.7922
0.4932
0.2541
0.2431
0.0032
Physical inactivity (n [%])11 [2.1]10 [3.5]184 [2.8]18 [3.8]11 [4.1]283 [5.0]
Daily smoking (n [%])92 [17.4] 60 [21.0] 1661 [24.5] 70 [14.7]57 [21.3] 1046 [18.4]
Alcohol abstainers(n [%])18 [3.4] 14 [4.9] 263 [4.0]9 [1.9]5 [1.9]123 [2.2]
BMI (mean [SD])
BMI ≥30 kg/m2(n [%])
26.6 [4.1]27.8 [4.9]27.5 [4.6] 27.3 [3.1]27.9 [3.9] 27.9 [3.6]
110 [20.8]79 [27.6] 1761 [26.0]93 [19.5]69 [25.7] 1413 [24.9]
Headache(n [%])192 [42.5]79 [36.1] 2177 [38.2] 120 [29.1]60 [29.4]1298 [27.9]
Musculoskeletal pain(n [%]) 286 [63.4]141 [64.7] 3576 [62.3]200 [47.8] 108 [52.4]2351 [50.4]
HADS A score(mean [SD])4.0 [3.5]4.5 [3.5] 4.3 [3.5]3.2 [2.8]3.6 [3.1]3.5 [3.1]
HADS D score(mean [SD])2.9 [2.6]3.0 [2.6] 3.3 [2.9]3.4 [2.9]3.7 [2.9] 3.7 [2.9]
Antihypertensive use (n [%]) 101 [19.1]54 [18.9] 1638 [24.2]93 [19.5]60 [22.4]1495 [26.3]
Laboratory measurements
SBP (mean [SD])129.7 [17.1]132.0 [19.3]132.2 [18.7] 0.0061
0.0042
0.4851
0.8302
0.0551
0.5892
0.3641
0.1341
0.0181
0.0092
134.2 [16.5] 136.0 [17.8]135.4 [17.0] 0.2771
0.7922
0.2781
0.8162
0.0011
0.0032
0.1031
0.0551
0.0391
0.0162
SBP ≥140 mmHg (n [%])136 [25.8] 100 [35.7]1880 [32.2]165 [35.2]96 [36.1]1805 [36.7]
DBP (mean [SD]) 73.2 [10.5]74.1 [10.9] 73.5 [10.5]79.9 [9.9] 80.9 [10.0]79.9 [10.2]
DBP ≥90 mmHg (n [%])34 [6.4] 21 [7.5]387 [6.6]71 [15.1] 43 [16.2]798 [16.2]
Cholesterol (mean [SD])5.9 [1.1]5.8 [1.1]6.0 [1.1]5.5 [1.0]5.4 [1.0]5.6 [1.0]
High cholesterol (n [%])149 [30.1] 79 [30.0]2120 [31.9]75 [16.5]33 [13.3] 1152 [20.5]
HDL Cholesterol(mean [SD])1.5 [0.4] 1.5 [0.4]1.5 [0.4] 1.2 [0.3]1.2 [0.3]1.2 [0.3]
Triglycerides (mean [SD])1.5 [0.8]1.6 [0.9]1.6 [0.9]1.8 [1.0]1.9 [1.2]1.9 [1.2]
Glucose (mean [SD])5.4 [1.5]5.6 [1.4]5.6 [1.4]5.8 [1.8]5.7 [1.6]6.0 [1.8]
Glucose ≥5.6 mmol/l (n [%])76 [15.4]48 [18.3] 1387 [20.9]125 [27.5] 60 [24.1]1763 [31.3]
1. One-way analysis-of-variance 2. Chi-squared test.
BMI: Body mass index; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; Fair or poor health: Fair or poor self-perceived health; Antihypertensive use:
Current use of antihypertensive medication; Glucose: Non-fasting glucose; High Cholesterol: Cholesterol ≥6.6 mmol/l.
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indication less psychological symptoms. It appears that
most of the differences were present at all survey points.
However, cholesterol and HADS-score were only available
from the last two surveys, therefore, it is difficult to ascer-
tain differences between the groups with regard to these
factors were present from the first study or had developed
over time.
The main objective of this study of non-participants
was to enable a careful evaluation of the generalizability
of results from future MRI-HUNT analyzes, which has
rarely been possible in previous population-based MR-
studies [2]. Strengths of the study were the large number
of participants, the population-based design, and the
long follow-up (>20 years) with three data points for
each participant.
A limitation of the study was that some questions were
not filled out by every participant, but the problem with
missing data was not extensive on each question, and
was unlikely to influence results. It should be noted that
66 out of 1560 eligible and selected candidates were not
invited due to stratification, but we had to count them
as invited, because it was impossible to trace them in
the de-identified data file. We cannot see that this could
markedly influence the results. One may also note that
all three groups consisted of individuals who had
participated in all three HUNT-studies and therefore
might be more compliant than the rest of the popula-
tion. Also, multiple comparisons increase the risk of type
I error. To avoid false positive results, a Bonferroni-
adjusted p-value of 0.001 was chosen for the univariate
analyses.
Participation rates have declined in HUNT 1, 2 and 3
(88%, 71% and 54%). Such decline in epidemiological stud-
ies seems to be a general tendency in later years [1].
Therefore, it has become increasingly important to analyze
characteristics of non-participants. However, evaluation of
non-participants in MRI studies is in general lacking, and
if done, is mostly restricted to demographic variables [14].
A Finnish study examining non-participation rates among
patients with psychiatric illnesses suggested that subjects
with psychosis were less likely to participate in an MRI-
study [15]. Similarly, in the present study participating
women had lower HADS-D than non-participating, pos-
sibly indicating a lower burden of psychiatric illness. One
may speculate whether subjects with higher level of anxiety
or depression tend to avoid MRI for fear of the investiga-
tion itself, or of the result.
There is a considerable decline in participation rates
from the first to the last HUNT study. It seems that the
reasons for not participating were quite similar in
Table 4 Odds ratio (OR) with 95% confidence interval (CI) for participants (MRI-p), non-participants (MRI-np) and non-
invited (MRI-ni) related to various health-related variables and adjusted for age and education
VARIABLESWOMENMEN
MRI-pMRI-npMRI-niMRI-pMRI-np MRI-ni
HUNT 1
BMI (≥30 kg/m2vs. <30 kg/m2)
OROR (95% CI)OR (95% CI)OROR (95% CI) OR (95% CI)
1.00 3.38 (1.39-8.21)** 2.53 (1.24-5.16)*1.004.97 (1.89-13.07)** 2.86 (1.26-6.50)*
SBP (≥140 mmHg vs. <140 mmHg) 1.001.48 (0.82-2.70) 1.25 (0.84-1.86)1.000.87 (0.57-1.35) 1.15 (0.89-1.49)
Non-employed (yes vs. no)1.001.05 (0.41-2.71)1.59 (0.88-2.87)1.000.48 (0.13-1.73)1.06 (0.57-1.98)
HUNT 2
BMI (≥30 kg/m2vs. <30 kg/m2)1.00 2.07 (1.34-3.21)**1.63 (1.19-2.23)**1.001.78 (1.12-2.82)*1.54 (1.11-2.13)**
SBP (≥140 vs. <140 mmHg)1.00 1.82 (1.26-2.62)** 1.52 (1.19-1.95)**1.00 1.27 (0.91-1.76)1.30 (1.06-1.61)*
Total Cholesterol (≥6.6 vs. <6.6)1.00 0.98 (0.67-1.43)1.05 (0.83-1.32)1.000.82 (0.57-1.17) 1.12 (0.90-1.39)
HADS D score (≥5.0 vs. <5.0)1.00 0.98 (0.69-1.39) 1.21 (0.98-1.50)1.000.83 (0.59-1.17) 1.02 (0.83-1.26)
Non-employed (yes vs. missing)1.00 1.05 (0.43-2.55)1.11 (0.64-1.93) 1.001.76 (0.61-5.10)1.38 (0.64-2.99)
HDL-Cholesterol (≥1.6 vs. <1.6)1.000.76 (0.56-1.02)0.99 (0.82-1.18)1.00 1.19 (0.76-1.88)1.51 (1.13-2.03)**
HUNT 3
BMI (≥30 kg/m2vs. <30 kg/m2) 1.001.45 (1.04-2.04)*1.21 (0.97-1.51) 1.00 1.37 (0.96-1.96)1.30 (1.03-1.65) *
SBP (≥140 vs. <140 mmHg)1.00 1.64 (1.19-2.26)** 1.25 (1.02-1.54)*1.001.08 (0.79-1.49)1.05 (0.86-1.29)
Total Cholesterol (≥6.5 vs. <6.5) 1.00 1.02 (0.73-1.41) 1.07 (0.88-1.31)1.00 0.79 (0.51-1.23)1.32 (1.02-1.71)*
HADS D score (≥5.0 vs. <5.0)1.001.12 (0.77-1.63)1.30 (1.04-1.63)*1.001.28 (0.90-1.83) 1.14 (0.92-1.42)
Non-employed (yes vs. no) 1.001.73 (1.19-2.51)**1.27 (0.99-1.62)1.000.90 (0.57-1.42) 1.16 (0.88-1.54)
HDL-Cholesterol (≥1.7 vs. <1.7)1.000.87 (0.63-1.20)0.93 (0.77-1.14) 1.001.20 (0.63-2.29) 1.69 (1.12-2.56)*
*p <0.05 ** P <0.01.
BMI: Body mass index; SBP: Systolic blood pressure.
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HUNT 1 and 2, but with some differences. In both,
being busy and having moved were the main reasons,
but having health problems were specific for HUNT 1,
and forgetting the invitation and not having the desire to
participate, were only reported in HUNT 2. Self-
reported reasons for not participating are not available
in HUNT 3. Thus it is not possible to ascertain whether
the reasons for not participating differed from those in
the first two studies.
There were slight, but significant, differences with re-
gard to clinical characteristics and presence of risk fac-
tors between the three groups. This finding shows the
need to take into account differences in risk factor pro-
files at baseline in participants versus non-participants
in future population based MRI studies. Importantly,
power might be weakened due to lower prevalence of
people with risk factors in the study population. This
will, however, not have any effect on associations or risk
analyses. One of the exclusion criteria was weight
>150 kg, but this probably does not explain the lower
BMI among participants, since only one individual was
above this weight in HUNT 3.
However, place of living within Nord-Trøndelag is a
factor that probably accounts for part of the difference.
In the MRI-HUNT study, the participants had to live
<45 minutes of travel from the town where the scans
were performed (Levanger), due to budget restraints,
and to increase participation. In all three HUNT-studies,
a higher proportion with obesity and lower education
levels has been found in rural communities [8], and the
higher BMI may also explain the higher BP and choles-
terol among MRI-ni.
This cannot explain differences between MRI-np and
MRI-p, because both groups lived in the same area. The
lower level of education and increased BMI and BP
among MRI-np may be explained by generally lower
participation rates among individuals with lower educa-
tion and poorer health [16]. Conceivably, higher BMI
among MRI-np compared to MRI-p may also be a result
of overweight people, even those well below 150 kg, tend
to refrain from participation in fear of being too big for
the scanner. Different proportions of obese individuals
might further have contributed to differences in other
health related measures (cholesterol and BP).
Cardiovascular risk factors (like obesity and hyperten-
sion) are related to a risk of stroke and TIA, and also to
alterations in brain morphometry [17-25].Lower partici-
pation rates among those with high cardiovascular risk
could therefore lead to an underestimation of vascular
brain changes in the general population. The prevalence
of these changes in the MRI-p will therefore most prob-
ably represent the minima, and to some extent one can
correct for the bias. In other population-based MRI-
studies, various types of bias may be present, probably
related to the mode of recruitment and a host of other
factors, but their direction and magnitude are largely
unknown.
Conclusions
Self-reported health did not differ between participants,
non-participants and non-invited, but, participants had
higher education level, lower BMI, lower BP, and were
somewhat younger. The observed differences between
participants and non-invited individuals are probably
partly explained by the inclusion criterion that partici-
pants had to live within 45 minutes of transport to the
hospital where the MRI examination took place. Since
increased BMI and BP impact brain morphometry, this
should be taken into consideration and preferably cor-
rected for when the results of the MRI-HUNT will be
published. Because the generalizability of results may be
influenced by selective participation, we recommend that
non-participation studies in MRI research should be
mandatory.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
LMH contributed to designing the study, analyzing the data, interpreting the
results and writing and revising the article. ML contributed to designing the
study, interpreting the results and revising the article. AH contributed to
collecting the data, designing the study, interpreting the results and revising
the article. LJS was leader of the MRI-HUNT-study, and contributed to
designing the study, interpreting the results and revising the article. KH
contributed to designing the study, applying for data access, analyzing the
data, interpreting the results and writing and revising the article. All authors
have read and approved the final manuscript.
Acknowledgements
The Nord-Trøndelag Health Study (HUNT) is a collaboration between the
HUNT Research Centre, Faculty of Medicine at the Norwegian University of
Science and Technology (NTNU), the Norwegian Institute of Public Health
and the Nord-Trøndelag County Council. The staff at the Department of
medical imaging, Levanger hospital.
Author details
1Department of Neuroscience, Norwegian University of Science and
Technology, Trondheim 7491, Norway.2Norwegian National Headache
Centre, St. Olavs University Hospital, Trondheim, Norway.
Received: 18 May 2012 Accepted: 17 July 2012
Published: 30 July 2012
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doi:10.1186/1471-2342-12-23
Cite this article as: Honningsvåg et al.: Does health differ between
participants and non-participants in the MRI-HUNT study, a population
based neuroimaging study? The Nord-Trøndelag health studies 1984–
2009. BMC Medical Imaging 2012 12:23.
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