Scandinavian Journal of Public Health, 2011; 39(Suppl 7): 131–135
APPLICATIONS OF DANISH REGISTERS IN RESEARCH
The Danish National Cohort Study (DANCOS)
MICHAEL DAVIDSEN, METTE KJØLLER & KARIN HELWEG-LARSEN National Institute of Public Health, University of Southern Denmark, DK-1353 Copenhagen K, Denmark
Abstract Introduction: The Danish National Cohort Study (DANCOS) is a nationally representative public health survey based on linkage of information in the repeated Danish Health Interview surveys, 1986–2005, to the national Danish registers on health and welfare. It facilitates studies of self-reported health behaviour and utilisation of healthcare services by subgroups and analysis of non-response bias. Research topics: DANCOS data are utilised in a variety of analyses presented here by a few examples that emphasise the impact of modifiable risk factors on public health, description of non-response bias, and the epidemiology of chronic pain and of osteoarthritis. Examples of DANCOS-based results are shown for each of the four topics. Smoking results in 24% of all deaths and, compared to other risk factors for public health, smoking accounts for the highest number of years of life lost. For non-response the mortality is higher among non-respondents than among respondents, but no significant bias on healthcare estimates can be seen. On average individuals with chronic pain had 12.8 contacts per year to the primary healthcare sector compared with 7.3 for individuals without. For osteoarthritis it is estimated that in 2020 there will be 22,600 incident cases. Conclusion: DANCOS is a public health survey linked with registers with many research possibilities. With this article we hope to stimulate further interest in the survey.
Key Words: Epidemiology, health interview survey (HIS), official registers, public health
Introduction The DAnish National COhort Study (DANCOS) is a nationally representative public health survey administered by the National Institute of Public Health, University of Southern Denmark. The survey combines individual-based information from the Danish Health Interview Surveys (DHIS) [1,2] (former named the national Danish Health and Morbidity Surveys) and official Danish registers on health and welfare, many of which are described in this supplement and which are presented in Figure 1. Further to this, DANCOS contains the register-based information from Figure 1 for the entire adult (age 16þ) Danish population. The survey has previously been described [3]. The main purpose of the DHIS is to describe the status and trends in health and morbidity in the adult Danish population and factors having an influence
upon public health [1]. The results are used in national, regional, and municipal healthcare planning and prevention programmes. The concepts of health and morbidity are broadly defined in the surveys and this is reflected in the way DANCOS data have been applied. Thus, DANCOS is used in public health research, for example in analyses of the costs of heart disease [4,5], in comparisons of self-reported and register-based information [6,7], and in descriptions of the magnitude of suicide, suicide attempts, and suicide ideation in the Danish population [7–9]. In this paper we highlight four research topics where DANCOS data have been used: the impact of modifiable risk factors on public health [10], a description of non-response [11,12], and the epidemiology of chronic pain [13] and of osteoarthritis [14]. These choices are motivated as follows: politicians, civil authorities, and health professionals request high-quality data for the planning of healthcare
Correspondence: Michael Davidsen, National Institute of Public Health, University of Southern Denmark, Øster Farimagsgade 5A, DK-1353 Copenhagen K, Denmark. E-mail:
[email protected] (Accepted 11 January 2011) ß 2011 the Nordic Societies of Public Health DOI: 10.1177/1403494811399167
132
M. Davidsen et al. The Danish Civil Registration System
The Register of Causes of Death
The Danish National Patient Register
The Danish National Health Service Register
Danish registers of crime
Registers on place and country of birth
DANCOS All persons invited to participate in the Danish Health Interview Surveys 1987, 1991, 1994, 2000 and 2005. Adult Danish Population.
The Danish National Prescription Registry
The Building and Housing Register
N = 57,111
Registers on personal level of education
The Danish Cancer Registry
The Danish Psychiatric Central Research Register
Danish registers on personal income and transfer payments
Danish registers on personal labour market affiliation
Figure 1. Official registers linked with the Danish Health Interview Surveys (DANCOS).
services and general health promotion. The comprehensive DANCOS data make it possible to measure the effect of a number of modifiable health risk factors and, hence, present a solid basis for public health promotion. The representativeness of respondents is a key issue in all surveys [15]. Randomisation usually ensures that a survey is representative of an a-priori well-defined target population, but the results may be biased by the fact that for different reasons some of the persons invited choose not to respond. This problem is increasing as response rates are declining in many national and regional surveys [16]. DANCOS includes register-based information for both respondents and non-respondents, which renders it possible to carry out analysis of the bias related to non-respondents. The Danish Health Interview Surveys in 2000 and 2005 included questions about the prevalence of chronic pain. Consequently, DANCOS presents data that can contribute to describe the epidemiology and the socioeconomic burden of this condition. As in other countries, osteoarthritis is a cause of disability in the elderly population in Denmark [17]. Recently, DANCOS data were used to describe the trends in the epidemiology of this condition in Denmark and the impact of various risk factors on the trends among men and women [14].
The Danish Health Interview Surveys The National Institute of Public Health has conducted nationally representative surveys of the adult (age 16þ) Danish population in 1987, 1994, 2000, and 2005. Invited persons were selected at random. The surveys in year 2000 and 2005 comprised a reinterview of persons invited to the survey in 1994. All persons agreeing to respond had a personal interview in their home and, except in 1987, upon completion of the interview were asked to fill out a selfadministered questionnaire. The interview included questions on health, life-style, healthcare contact, illness and illness behaviour, and several other issues. Core questions were asked during the interview in all four surveys, while more specialised and sensitive questions were asked in the self-administered questionnaire [1,2]. In 1991, a special survey on muscular-skeletal diseases was conducted.
Research topics Impact of modifiable risk factors on public health DANCOS data have been an essential tool in calculating the impact of risk factors upon mortality, morbidity and the use of healthcare services, mainly
The Danish National Cohort Study (DANCOS)
133
Smoking Short education Alcohol Physical inactivity Hypertension Psychosocial job strain Overweight Occupational diseases Drug abuse Home and leisure accidents Passive smoking Weak social relations (rarely meet family) Unhealthy diet (too little fruit and vegetables) Unhealthy diet (too much saturated fat) Traffic accidents Men Women
Weak social relations (no help from others) Unsafe sex Occupational accidents 0
20,000 40,000 60,000 80,000 100,000 120,000 Number of years of life lost
Figure 2. Years of life lost in Denmark related to various risk factors. Annual number of years of life lost for men and women. (Reproduced from Juel K, Sørensen J and Brønnum-Hansen H. Risk factors and public health in Denmark. Scand J Public Health 2008; 36(Suppl 1):11–227).
using the DHIS in year 2000 and the Register of Causes of Death, the Danish National Patient Register, and the Danish National Health Service Register. Very few countries possess similar data that enable direct analyses of various risk factors, indicators of public health and social-economic costs. Based on DANCOS, the National Board of Health and the National Institute of Public Health have recently analysed 19 selected risk factors’ individual impact on 18 different public health indicators [10]. The risk factors included for example smoking, physical inactivity, unsafe sex, and low educational level. The public health indicators comprised healthy life expectancy, disability pensions, and health service costs. The impact of various risk factors on the number of years of life lost is compared in Figure 2. Smokingrelated deaths account for the highest number of years of life lost and the most among men. Furthermore, the report stated that smoking is responsible for 24% of all deaths, resulting in 215,000 years of life lost. Heavy smokers may expect 10–11 fewer quality-adjusted life years. Smoking also results in 17% of all hospital admissions and 8% of all contacts to general practitioners, as well as 2.8 million days lost to sickness absence and almost 5000 disability pensions per year. Smoking
raises health service costs by almost DKK 4.5 billion per year and the net health service costs related to smoking amount to DKK 3.4 billion per year. The recommendations of the Danish Commission of Prevention are to a large extent based on these DANCOS analyses [18].
Description of non-response bias When performing surveys of a population an inherited problem is non-response, i.e. the fact that some persons for different reasons choose not to respond. It is well known that this may cause biased results [15,19] especially if the non-response is high [20], raising concerns about the representativeness of the results. It has been shown that changes in nonresponse rates do not necessarily alter exposureoutcome associations or point estimates [19,21], but bias arises if data are not missing completely at random, i.e. if some groups have different nonresponse than others. Danish legislation permits individual-based record linkage to official Danish registers for both respondents and non-respondents, thus presenting the unique possibility of register-based comparisons of these two groups.
134
M. Davidsen et al.
Using the Danish Civil Registration System, Andersen et al. [22] have shown higher mortality rates among non-respondents than among respondents – a finding also seen in DANCOS [3]. One obvious explanation for this might be higher morbidity rates among non-respondents than respondents. Using DANCOS data from the Danish National Patient Register it has been shown [11] that nonrespondents and respondents had identical hospital admission rates 5 years before and 2 years after data collection. Non-respondents had a significantly higher hospitalisation rate only immediately before and during data collection. The bias of the non-response may be determined by the multiplicative effect of the proportion of non-respondents and the difference between the respondents and the non-respondents. Furthermore, different types of non-response may have different effects on the magnitude and direction of the bias [19]. When including costs from the Danish National Patient Register, the Danish National Health Service Register, and the National Prescription Registry, Gundgaard et al. [12] concluded that different types of non-response have different bias effects. They demonstrated that although the ill constitute only about 1%, the large differential in healthcare utilisation costs between the interviewed and the ill contributes considerable to the non-response bias component.
Epidemiology of chronic pain People with chronic pain are among the most frequent users of the healthcare system and it has been suggested that the costs of health care for patients of this category exceed the combined costs of treating patients with coronary artery disease, cancer, and AIDS [23]. A one-dimensional question on chronic pain was included in the self-administered questionnaire of the DHIS year 2000 and DHIS 2005 [24–26] and the data have been used in analyses of life-style [27], and the use of pain killers [28] and to identify risk factors [29]. Based on DANCOS [23] it was shown that individuals reporting long-term pain on average have 12.8 contacts per year to the primary healthcare sector compared with 7.3 for individuals without pain. Furthermore, the hospital admission frequency and number of in-hospital days not only was highest for the pain group, but the difference also increased during the periods investigated.
Epidemiology of osteoarthritis Muscular-skeletal diseases represent a heavy burden on the healthcare system and result in impaired quality of life for the patients. Recently, we conducted an epidemiological analysis of osteoarthritis with an emphasis on the modifiable risk factors [14]. In Denmark, the incidence of osteoarthritis is 23.9 for men and 35.3 for women per 10,000 person years and it is highest among the elderly. In the period 1994–2007, the incidence remained unchanged. For both men and women, the most important modifiable risk factor seems to be overweight. Using predicted trends in overweight from DHIS and future population size and composition from Statistics Denmark the number of new cases of osteoarthritis in Denmark was estimated to be 22,600 in 2020 (13,600 women and 9000 men). Based on data from the entire Danish population, an analysis of the occupational risk of osteoarthritis for men showed a four times higher risk of osteoarthritis among floor workers, persons in transportation, in construction and in agriculture compared to a control group of office assistants.
Conclusion DANCOS is a valuable data source that has been used in a large number of studies, of which we have presented a few examples. DANCOS’ unique linkage of data in the repeated national representative health interview surveys, 1987–2005, and in Statistic Denmark’s registers facilitates studies of the broad range of health issues that is covered by the DHIS. We hope with this review to have increased the interest in the survey and thereby to have encouraged further use of this unique national survey.
Funding This research received no specific grant from any funding agency in the public, commercial, or notfor-profit sectors.
References [1] Rasmussen NK, Kjøller M. ‘‘[The National Institute of Public Health’s program for health and morbidity surveys]’’. Ugeskr Laeger 2004;166:1438–41. [2] Ekholm O, Hesse U, Davidsen M, Kjøller M. The study design and characteristics of the Danish National Health Interview Surveys. Scand J Public Health 2009;37:758–65. [3] Davidsen M, Helweg-Larsen K, Kjøller M. [DANCOS – a register follow-up of the national Danish health and morbidity surveys]. Ugeskr Laeger 2004;166:1441–4.
The Danish National Cohort Study (DANCOS) [4] Kruse M, Davidsen M, Madsen M, Gyrd-Hansen D, Sorensen J. Costs of heart disease and risk behaviour. Implications for expenditure on prevention. Scand J Public Health 2008;36:850–6. [5] Kruse M, Sørensen J, Davidsen M, Gyrd-Hansen D. Short and long-term labour market consequences of coronary heart disease: a register-based follow-up study. Eur J Cardiovasc Prev Rehabil 2009;16:387–91. [6] Nielsen MW, Søndergaard B, Kjøller M, Hansen EH. Agreement between self-reported data on medicine use and prescription records vary according to method of analysis and therapeutic group. J Clin Epidemiol 2008;61:919–24. [7] Helweg-Larsen K, Kjøller M, Juel K, Sundaram V, Laursen B, Kruse M, et al. [Suicides in Denmark. Marked decrease in suicides but increase in suicide attempts. Why?] København: Statens Institut for Folkesundhed, 2006. [8] Norlev J, Davidsen M, Sundaram V, Kjøller M. Indicators associated with suicidal ideation and suicide attempts among 16–35-year-old Danes: a national representative population study. Suicide Life Threat Behav 2005;35:291–308. [9] Norlev J, Davidsen M, Kjøller M. Six year follow-up of health status: changes in Danish adults with suicidal tendency in 1994. Suicide Life Threat Behav 2006;36(1): 103–12. [10] Juel K, Sørensen J, Brønnum-Hansen H. Risk factors and public health in Denmark. Scand J Public Health 2008; 36(Suppl 1):11–227. [11] Kjøller M, Thoning H. Characteristics of non-response in the Danish Health Interview Surveys, 1987–1994. Eur J Public Health 2005;15:528–35. [12] Gundgaard J, Ekholm O, Hansen EH, Rasmussen NK. The effect of non-response on estimates of health care utilisation: linking health surveys and registers. Eur J Pub Health 2008;18:189–94. [13] Eriksen J, Sjøgren P, Ekholm O, Rasmussen NK. Health care utilisation among individuals reporting long-term pain: an epidemiological study based on Danish National Health Surveys. Eur J Pain 2004;8:517–23. [14] Helweg-Larsen K, Davidsen M, Laursen B, Andersen S. [Osteoarthritis. Prevalence and risk factors – development in Denmark]. Statens Institut for Folkesundhed 2009. [15] Biemer PP, Lyberg L. Introduction to survey quality. New York: Wiley; 2003. [16] de Heer W. International response trends: results of an international study. J Off Stat 1999;15:129–42.
135
[17] Bedson J, Jordan K, Croft P. The prevalence and history of knee osteoarthritis in general practice: a case-control study. Fam Pract 2005;22:103–8. [18] Forebyggelseskommissionen: [We can live longer and more healthy. Recommendations from Commission and Prevention on improved preventive initiatives 2009]. Forebyggelseskommissionen, Ministeriet for Sundhed og Forebyggelse. Betænkning 1506. Available from: www.forebyggelseskommissionen.dk [19] Groves RM, Couper MP. Nonresponse in household interview surveys. New York: Wiley Interscience; 1998. [20] Hupkens CL, van den Berg J, van der Zee J. National health interview surveys in Europe: an overview. Health Policy 1999;47:145–68. [21] Stang A, Jo¨ckel KH. Studies with low response proportions may be less biased than studies with high response proportions. Am J Epidemiol 2004;159:204–10. [22] Andersen LB, Vestbo J, Juel K, Bjerg AM, Keiding N, Jensen G, et al. A comparison of mortality rates in three prospective studies from Copenhagen with mortality rates in the central part of the city, and the entire country. Eur J Epidemiol 1998;14:579–85. [23] Eriksen J, Sjøgren P, Ekholm O, Rasmussen NK. Health care utilisation among individuals reporting long-term pain. An epidemiological study based on Danish National Health Surveys. Eur J Pain 2004;8:517–23. [24] Eriksen J, Jensen MK, Sjøgren P, Ekholm O, Rasmussen NK. Epidemiology of chronic non-malignant pain in Denmark. Pain 2003;106:221–8. [25] Jensen MK, Sjøgren P, Ekholm O, Rasmussen NK, Eriksen J. Identifying a long-term/chronic, non-cancer pain population using a one-dimensional verbal pain rating scale. An epidemiological study. Eur J Pain 2004;8:145–52. [26] Sjøgren P, Ekholm O, Peuckmann V, Grønbæk M. Epidemiology of chronic pain: An update. Eur J Pain 2009;13:287–92. [27] Ekholm O, Grønbæk M, Peuckmann V, Sjøgren P. Alcohol and smoking behavior in chronic pain patients: the role of opioids. Eur J Pain 2009;13:606–12. [28] Eriksen J, Sjøgren P, Bruera E, Ekholm O, Rasmussen NK. Critical issues on opioids in chronic non-cancer pain: an epidemiological study. Pain 2006;125:172–9. [29] Eriksen J, Ekholm O, Sjøgren P, Rasmussen NK. Development of and recovery from long-term pain. A sixyear follow-up study of a cross section of the adult Danish population. Pain 2004;108:154–62.
