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Study design, participation and characteristics of The Danish General Suburban Population Study

Helle K.M. Bergholdt,1, 5 Lise Bathum,1, 2, 3 Jan Kvetny,2, 4, 5 Dorthe B. Rasmussen,2, 6 Birgitte Moldow,2, 7 Tracy Hoeg,5, 7 Gregor B.E. Jemec,5, 8Helle Berner-Nielsen,1, 2 Børge G. Nordestgaard5, 9, 10 & Christina Ellervik1, 2, 5 1) Department of Clinical Biochemistry, Naestved Hospital2) The Danish General Suburban Population Study, Naestved Hospital3) The Faculty of Health Sciences, University of Southern Denmark4) Department of Internal Medicine, Naestved Hospital5) The Faculty of Health and Medical Sciences, University of Copenhagen6) Center for Disease and Health, Naestved Municipality7) Department of Ophthalmology, Naestved Hospital8) Department of Dermatology, Roskilde Hospital9) Department of Clinical Biochemistry, Herlev Hospital10) The Copenhagen General Population Study, Herlev Hospital


Introduction: The aim of this article was to describe the study design, participants and baseline characteristics of The Danish General Suburban Population Study (GESUS) and to compare suburban participants with age- and gender-matched urban participants from the Copenhagen General Population Study (CGPS).

Material and methods: Data from questionnaire, health examination, biochemical measurements and public registers were collected.

Results: In GESUS the overall participation rate was 49.3% (response n = 10,621 of total n = 21,557). Among people aged 40-79 years, the participation rate was 53.9% (8,797/16,310). Participants were more frequently women, had a higher median age, a higher frequency of marriage/registered partnerships, but had a lower frequency of co-morbidities and death in the follow-up period (January 2010-May 2011 (diseases)/June 2011 (death) than the non-participants. GESUS has sufficient power to study effects of rare and common exposures or genetic variants on the occurrence of common multifactorial diseases. Compared with an age- and gender-matched urban population (n = 10,618, CGPS), participants in GESUS (n = 10,618) were less physically active, smoked less and ingested less alcohol, had higher anthropometric measures, less undiagnosed hypertension but more undiagnosed diabetes, had a lower frequency of elevated total cholesterol and low-density lipoprotein cholesterol but higher frequency of decreased high-density lipoprotein cholesterol and elevated triglycerides.

Conclusion: In GESUS, participants had a better health profile than non-participants, and participants in GESUS had a different cardiovascular risk profile than participants in the CGPS.

Funding: The study received funding from the following: Johan and Lise Boserup Foundation; TrygFonden; Det Kommunale Momsfond; Johannes Fog’s Foundation; Region Zealand; Region Zealand Foundation; Naestved Hospital; Naestved Hospital Foundation; The National Board of Health; Danish Agency for Science, Technology and Innovation.

Trial registration: not relevant.

The Danish General Suburban Population Study (GESUS) is a study of the general suburban population living in Naestved Municipality (70 km south of Copenhagen). The aim of GESUS is to facilitate epidemiologic and genetic research by using information from questionnaires, health examinations, biochemical measurements, genetic variants and public registers to analyze the occurrence of co-morbidities (e.g. diabetes, cardiovascular disease, pulmonary disease and cancer) and mortality.

The aim of this article is to describe the study design, participants and baseline characteristics of GESUS and to compare the suburban participants with urban participants from the Copenhagen General Population Study (CGPS).


Study population

GESUS was initiated in January 2010 with ongoing enrollment and is a cross-sectional study of the adult Danish suburban general population in Naestved Municipality (70 km south of Copenhagen; including postal codes 4160, 4171, 4250, 4262, 4684, 4700, 4733, and 4736). The criteria for invitation are Danish citizenship and a Danish Civil Registration number (CPR, a unique identification number assigned at birth to all Danes) indicating Danish residence. All persons aged 30+ and a random 25% selection of the population aged 20-30 years are invited by mail in numerical order starting with citizens born on the 1st in every month and continuing. If individuals have not responded within three weeks of their scheduled attendance period, a reminder is sent with a new scheduled period. A completed paper-questionnaire is a prerequisite for attending the health examination. For this study, we included participants and non-participants from 11 Jan 2010 to 31 July 2011.

The study was approved by the appropriate institutional review boards and ethical committees (SJ-113, SJ-114, SJ-147, SJ-278), and it was reported to the Danish Data Protection Agency. Written informed consent was obtained from all participants. The investigation conforms to the principles of the Declaration of Helsinki.

Self-administered questionnaire

The questionnaire was similar to the ones used for the Copenhagen City Heart Study (CCHS) and the CGPS [1], but it also included questions about skin and allergies [2-4], health-related information, well-being and depression [5, 6]. The questionnaire was tested in a pilot-study on 60 volunteers and finally validated by the Danish Unit of Patient Conceived Quality, Institute of Public Health.

Health examination

The health examination was carried out by trained health professionals at the Department of Clinical Biochemistry, Naestved University Hospital, Denmark, on weekdays 3.30 PM-9.00 PM.

After five minutes of rest, two consecutive digital measurements of blood pressure were performed on the left upper arm (apparatus type A&D UA-787, A&D Medical, Tokyo, Japan) [7], and the blood pressure of the second measurement was registered.

Using a tape measure, waist circumference (WC) (cm) was measured at the lowest rib and hip circumference (HC) (cm) at the widest part of the hip. Height (cm) was measured without shoes, using a stadiometer. Body composition (weight (kg), body fat, muscle mass, body water) was measured on a Bio Impedance Analysis (BIA) (TANITA MC-180MA; Tanita Corporation, Tokyo, Japan). However, participants with a pacemaker and pregnant women were weighed on an ordinary digital weight scale (Tanita WB-110 MA); 1 kg was subtracted to account for clothes.

Lung function and pulse-oximetry were measured by a hand-held Spirometer (MicroLoop, Micro Medical Ltd, Kent, UK) and considered valid if the “ATS/ERS quality criterion” by the American Thoracic Society (ATS) and the European Respiratory Society (ERS) was met [8].

A resting 12-lead electrocardiography (ECG) at 150 Hz (Mac-5500,GE Healthcare, Milwaukee, WI) was recorded and digital (MUSE/Interval Editor software (GE Healthcare, Milwaukee, WI) and paper versions (25 mm/sec.) filed. ECGs were coded according to the automatic ECG analysis programme (Marquette 12 SL revision E, GE Healthcare) and manually according to the Minnesota Coding System by two health examinators [9].

Distal blood pressure for the measurement of ankle-brachial index (ABI) was measured by standard Doppler technique using Dopplex mini (Huntleigh) and a manometer. ABI was the highest ankle pressure divided by the highest arm pressure after bilateral arm and ankle pressures [10].

Arterial stiffness, vascular tone and endothelial function were tested using Pulse Trace PCA2 (Micro Medical Ltd, Kent, UK) [11] which is a photoplethysmographic device placed at the finger-tip and like pulse-oximetry using peripheral waveform analysis.

The eye examination (the Danish Rural Eye Study (DRES)) included a structured interview, best corrected visual activity (Nidek Auto Refratometer 360-A) followed by an EDTRS chart when vision was < 20/25), testing of colour vision (Ishihara), testing for strabismus (Hirsnberg) and retinal photos of both eyes.

Body mass index (BMI) was calculated as kg/m2 and waist-hip-ratio (WHR) was calculated by WC/HC. Elevated WHR or WC was considered present in women with a WHR > 0.85 or a WC > 88 cm and men with a WHR > 0.90 or a WC > 102 cm [12].

Sample collection, blood analyses and storage conditions

Fresh blood samples (50 ml) were drawn in the non-fasting state. Venosafe plastic tubes (Terumo, Leuven, Belgium) were used and 25 ml of blood were spun and kept overnight at 4 ºC until biochemical analysis the next morning ( Supplementary Table 1). Assays were followed up daily for precision and several times annually for accuracy with a Scandinavian quality control programme. A total of 25 ml ethylenediaminetetraacetic acid (EDTA) whole blood and serum were kept overnight at 4C for aliquoting the next morning into 2 × 2 ml serum, 2 × 2 ml buffy coat, and 4 × 2 ml plasma and then stored at –80C for future research purposes. The duplicates were located in two geographically distant biobanks. DNA was extracted (2ml buffy coat yielded approximately 100 micrograms/participant) at KBiosciencie Laboratory (Hoddesdon,UK) and then stored at –80C at KBioscience and at Naestved University Hospital, Denmark. Spot urine samples (10 ml) were collected in Urine Monovette and spun and aliquoted on the examination day into a 1.2 ml tube and a 10 ml tube and temporarily stored at –80C until transfer of samples to The Laboratory for Clinical Pharmacology (University Hospital Copenhagen, Denmark) and stored at –80 ºC.

Low-density lipoprotein cholesterol (LDL-C) was calculated from the Friedewald equation if triglycerides (TG) was < 5 mmol/l [13]. TC ≥ 5 mmol/l, LDL-C ≥ 3 mmol/l, TG ≥ 2 mmol/L and high-density lipoprotein cholesterol (HDL-C) ≤ 1 mmol/l were indicative of high risk of cardiovascular disease [14]. Levels of blood glucose and HbA1c were considered elevated and indicative of diabetes if glucose ≥ 11 mol/l or HbA1c ≥ 48 mmol/mol.

Register-based data

The study included register-based data as follows: The Danish Cancer Registry (World Health Organization (WHO) International Classification of Diseases, Seventh Revision (ICD-7) and Tenth Revision (ICD-10) codes) [1]; the national Danish Patient Registry with diagnoses of ischaemic heart disease (ICD8: 410-414, ICD10: I20-I25), cerebrovascular disease (ICD8: 430-438, ICD10: I60-I68, G45), and diabetes (Type 1 diabetes (ICD8: 249, ICD10: E10) and Type 2 or other or unspecified diabetes (ICD8:250, ICD10: E11, E13, E14)); the national Danish Causes of Death Registry, the Danish Civil Registration System (marital status and mortality). Follow-up (Jan 2010-May 2011 (diseases)/June 2011 (death) was 100%.

Comparison population

The CGPS [1] has recruited participants randomly from the general population of Copenhagen, Denmark since 2003. It has a response rate of 49.3% (response n = 10,621 of total n = 21,557). We included age- and gender-matched participants (n = 10,618) for comparison with GESUS on baseline characteristics. The differences in number (10,621 versus 10,618) are due to lack of match for three participants in GESUS.

Identification and correction of errors

Data from GESUS were checked for serious errors and inconsistencies. Questionnaires were checked for missing data points on the day of attendance. Participants were rejected at the health examination until the questionnaire had been completed. With use of the mass verification function in ReadSoft, numbers for each questionnaire were visually inspected and if any discrepancies occurred, the original questionnaire was inspected and scanning errors corrected. All variables were checked for errors by category and range (minimum and maximum values).

A complete list of data errors and inconsistencies was produced for the whole study containing before- and after-values of the identified outliers. Other information available in the questionnaire was examined in order to judge the likelihood of the data in question being correct (internal validity). If a strong indication of serious error was present, the error was corrected provided the information needed was available or participants were contacted by telephone in order to retrieve the correct answer. In case of lack of response to the telephone call, the data inconsistencies were recoded to missing values. Biochemical and other health measurements were examined by range, and only extreme outliers incompatible with life (e.g. pulse < 10) were corrected or recoded as missing values. These errors were mostly due to the manual recording of data on the rare occasion of electronic database inaccessibility.


STATA 11.0 was used. Pearson’s χ2- and the Mann-Whitney-U tests were used for categorical and continuous variables, respectively. The level of significance was p < 0.05. The total numbers in the analyses vary slightly according to availability of data for each covariate. Power was calculated using NCSS-Pass.

Trial registration:


Characteristics of participants versus non-participants

The participation rate was 49.3% with10,621 participants and 10,936 non-participants (Figure 1). Among people aged 40-79 years, the participation rate was 53.9% (57.0% among women and 50.6% among men) (Figure 1). The participation rates were higher among women than among men, except for people aged 80+ years. Compared to non-participants, participants were more frequently women (54.8% versus 49%), had a higher median age (56 versus 52 years), a higher frequency of suburban residence, a higher frequency of marriage/registered partnerships (68.2% versus 51.7%) and a lower frequency of co-morbidities (cancer, cardiovascular disease, diabetes and hypertension) (26.6% versus 28.0%) and death in the follow-up period (0.3% versus 1.3%) (Table 1).

Study power

With 80% power, alpha = 0.05 and diseases occurring in 30%, 20% and 10% of participants, the minimal detectable odds ratios in GESUS among the participants included (n = 10,621) will be 3.3, 3.4 and 4.1 for rare (0.2%) exposures, and 1.3, 1.4 and 1.5 for common (5%) exposures. Correspondingly, the minimal detectable odds ratios in GESUS among participants aimed for (n = 25,000) will be 2.2, 2.3 and 2.8 for rare (0.2%) exposures, and 1.2, 1.2 and 1.3 for common (5%) exposures (Supplementary Table 2).

Lifestyle and health factors within a suburban and an urban population.

Compared to the urban population (n = 10,618, CGPS), the suburban participants (n = 10,618, GESUS) were less physically active, smoked less and ingested less alcohol (Table 2). Furthermore, they had higher anthropometric measures (BMI and WHR) (Table 3), less undiagnosed hypertension but more undiagnosed diabetes (Table 3), less frequency of elevated total and LDL-C but higher frequency of decreased HDL-C and elevated TG (Table 3).


The overall participation rate in GESUS (49%) resembles that of the CGPS (49%) [1]. Among people aged 40-79 years, the participation rate was 53.9%. Participation rates in general population studies in Europe vary from 10% [15] to 72% [16]. In Denmark, the typical age of retirement is 65 years and the high participation rate for this age group might signify that people have more time to participate or are healthier than participants aged 80+ years. Overall, the participation rate is generally high among people aged 40-79 years, which is the population of interest in most general population studies.

Participants in GESUS have less co-morbidity and are more often married/live in registered partnerships than non-participants; these results resemble those of other population-based studies [17]. However, assessment of the impact of a potential non-participation selection bias also depends on whether there is an association between non-participation and exposure.

We have calculated ORs at 80% power and alpha 0.05 for different ratios of exposure and endpoints. In order not to commit a Type II error, calculation of study power, n and effect size will be necessary in future association studies. A larger sample size will be needed in order to detect a rare co-morbidity for a rare exposure compared to a common co-morbidity for a common exposure.

Compared to the CGPS, participants in the GESUS had a different cardiovascular risk profile. Levels of TG are higher among participants in the GESUS, which is a cause for concern because high levels of TG is an important risk factor for cardiovascular disease [18]. Thus, stratified prophylaxis and targeted finding and treatment of these risk factors may be needed in the different areas. Other Scandinavian studies investigating rural, suburban and urban populations differ compared to this study and are not directly comparable [19, 20].

The strengths of the study include the mixed invitation pattern (by gender, age and residence) throughout the study period which eliminates confounding due to seasonal variation; a second invitation adding 8.3 percentage points to the participation rate; similar questions and data collection for the CCHS and the CGPS which makes direct comparisons possible; and a data handling process with error and inconsistency correction. The limitations of the study included the length of the questionnaire (20 pages), no availability of an internet-based questionnaire and no weekend examinations. These limitations may have made participants less comparable to the general population.


This paper presents the first baseline results of disease and risk factor prevalence in GESUS and the comparison of participants and non-participants contributes with information which is important for the design and interpretation of future studies within GESUS. Participants differ from non-participants with regard to sex, age, residence, marital status, morbidity and mortality, and participants overall seem to be in better health than non-participants. A comparison between data from GESUS and the CGPS indicates several differences between suburban and urban population studies.

Correspondence: Christina Ellervik, Department of Clinical Biochemistry, Naestved Hospital, 4700 Naestved, Denmark. E-mail:

Accepted: 24 June 2013

Conflicts of interest:Disclosure forms provided by the authors are available with the full text of this article at

Bib ref: 
Dan Med J 2013;60(9):A4693
  1. Ellervik C, Tybjaerg-Hansen A, Nordestgaard BG. Total mortality by transferrin saturation levels: two general population studies and a metaanalysis. Clin Chem 2011;57:459-66.

  2. Esmann S, Dufour DN, Jemec GB. Questionnaire-based diagnosis of hidradenitis suppurativa: specificity, sensitivity and positive predictive value of specific diagnostic questions. Br J Dermatol 2010;163:102-6.

  3. Dalgard F, Svensson A, Holm JO et al. Self-reported skin complaints: validation of a questionnaire for population surveys. Br J Dermatol 2003;149:794-800.

  4. Williams H, Robertson C, Stewart A et al. Worldwide variations in the prevalence of symptoms of atopic eczema in the International Study of Asthma and Allergies in Childhood. J Allergy Clin Immunol 1999;103(1 Pt 1):125-38.

  5. Bech P, Olsen LR. [Discovering depression]. Ugeskr Læger 2001;163: 1980-2.

  6. Folker H, Folker AP. WHO-5 as a simple method for measuring quality of life in daily psychiatric clinics. Ugeskr Læger 2008;170:830-4.

  7. Wan Y, Heneghan C, Stevens R et al. Determining which automatic digital blood pressure device performs adequately: a systematic review. J Hum Hypertens 2010;24:431-8.

  8. Miller MR, Crapo R, Hankinson J et al. General considerations for lung function testing. Eur Respir J 2005;26:153-61.

  9. Prineas RJCRSZZ. The Minnesota Code Manual of Electrocardiographic Findings. 2 ed. London, Springer Verlag, 2010.

  10. Eldrup N, Sillesen H, Prescott E et al. Ankle brachial index, C-reactive protein, and central augmentation index to identify individuals with severe atherosclerosis. Eur Heart J 2006;27:316-22.

  11. Wilkinson IB, Hall IR, MacCallum H et al. Pulse-wave analysis: clinical evaluation of a noninvasive, widely applicable method for assessing endothelial function. Arterioscler Thromb Vasc Biol 2002;22:147-52.

  12. World Health Organization. Waist circumference and waist–hip ratio: report of a WHO expert consultation, Geneva, 8–11 December 2008. WHO Library Cataloguing-in-Publication Data; 2008 B.C. Dec.

  13. Nordestgaard BG, Benn M. Fasting and nonfasting LDL cholesterol: to measure or calculate? Clin Chem 2009;55:845-7.

  14. Graham I, Atar D, Borch-Johnsen K et al. European guidelines on cardiovascular disease prevention in clinical practice: executive summary. Atherosclerosis 2007;194:1-45.

  15. Watts G. UK Biobank gets 10% response rate as it starts recruiting volunteers. BMJ 2007;334:659.

  16. Hofman A, van Duijn CM, Franco OH et al. The Rotterdam Study: 2012 objectives and design update. Eur J Epidemiol 2011;26:657-86.

  17. Bergstrand R, Vedin A, Wilhelmsson C et al. Bias due to non-participation and heterogenous sub-groups in population surveys. J Chronic Dis 1983;36:725-8.

  18. Kolovou GD, Mikhailidis DP, Kovar J et al. Assessment and clinical relevance of non-fasting and postprandial triglycerides: an expert panel statement. Curr Vasc Pharmacol 2011;9:258-70.

  19. Thelin N, Holmberg S, Nettelbladt P et al. Mortality and morbidity among farmers, nonfarming rural men, and urban referents: a prospective population-based study. Int J Occup Environ Health 2009;15:21-8.

  20. Svensson E, Reas DL, Sandanger I et al. Urban-rural differences in BMI, overweight and obesity in Norway (1990 and 2001). Scand J Public Health 2007;35:555-8.


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