copenhagen aging and midlife biobank (camb): an introduction

Journal of Aging and Health2014, Vol. 26(1) 5 –20

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Introduction

Copenhagen Aging and Midlife Biobank (CAMB): An Introduction

Kirsten Avlund, PhD, DMSc1,2,3, Merete Osler, PhD, DMSc1,2,3,4, Erik Lykke Mortensen, MSc1,2,5, Ulla Christensen, PhD1,2, Helle Bruunsgaard, PhD, DMSc6, Poul Holm-Pedersen, DDS, DrOdont1, Nils-Erik Fiehn, DDS, PhD, DrOdont1, Åse Marie Hansen, PhD1,8, Stine Harrsen Bachkati, MScPH1,2,3, Rikke Hodal Meincke, MScPH1,2, Eva Jepsen, OT1, Drude Molbo, PhD1, and Rikke Lund, MD, PhD1,2

Introduction

Since the early 1980s, a number of large-scale, population-based, epidemio-logic studies have focused on the development of disability, cognitive impair-ment, dementia, long-term care, and other health issues with particular relevance to older adults. With few exceptions, these health issues have been investigated in older populations, usually defined on the basis of chronologi-cal age (e.g., older than 65). Examples are the Established Populations for Epidemiologic Studies of the Elderly (EPESE), Women’s Health and Aging Studies (WHAS), and several other American, Australian, Canadian, and

1Department of Public Health, University of Copenhagen, Denmark2Center for Healthy Ageing, University of Copenhagen, Denmark3Danish Centre for Aging Research, University of Southern Denmark, Aarhus University and University of Copenhagen4Research Centre for Prevention and Health, Glostrup University Hospital, Denmark5Institute of Preventive Medicine, Bispebjerg Hospital, Capital Region of Denmark6Center of Inflammation and Metabolism, National University Hospital, Copenhagen Denmark7Department of Odontology, University of Copenhagen, Denmark8National Research Centre for the Working Environment, Copenhagen, Denmark

Corresponding Author:Rikke Lund, MD, PhD, Department of Public Health, University of Copenhagen, Oster Farimagsgade 5, P.O. Box 2099, Copenhagen, DK-1014 K, Denmark.Email: [email protected]

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European studies. Other studies have focused on even older ages to investi-gate age-associated changes in health (Health ABC, centenarian studies).

While this research has produced invaluable information on the health risks and outcomes during later periods of life, it has become increasingly evident that the initial signs of age-associated changes in health appear well before older age, and often develop in earlier stages of adulthood. Moreover, there is growing evidence that early-life risk factors affect late-life chronic disease, disability, and cognitive decline as much as similar risk exposures later in life itself, consistent with the life-course perspective in chronic dis-ease epidemiology (Kuh, 2007). The majority of studies underlying this evi-dence focused on the influence of early life factors on midlife physical and cognitive performance in midlife. First, several studies have shown that early biological factors (e.g., birth weight and childhood growth) are related to midlife physical capability (e.g., Kuh et al., 2002; Kuh et al., 2006). Second, it has been shown that childhood socioeconomic position is associated with a range of health outcomes in adult life, including coronary heart disease (Lawlor, Ebrahim, & Davey Smith, 2005),objectively measured physical capability (Birnie et al., 2011), lung function (Packard et al., 2011), decreased cognitive performance (Haan, Al-Hazzouri, & Aiello, 2011; Packard et al., 2011), and mortality (Galobardes, Lynch, & Smith, 2008; Osler, Andersen, Lund, & Holstein, 2005). Specifically, high educational attainment has been strongly associated with better cognitive performance in older adulthood (Clouston et al., 2012). Third, childhood cognitive ability has been adversely associated with the metabolic syndrome (R. M. Richards et al., 2009), physi-cal performance (Kuh, Cooper, Hardy, Guralnik, & Richards, 2009), cogni-tive decline (M. Richards & Wadsworth, 2004), and mortality in midlife (Calvin et al., 2011), but most of these effects were explained by effects of educational level and/or adult social class. However, several of these associa-tions are still poorly understood, and there is still a need for further explora-tion of possible critical and sensitive periods as well as the accumulative effects of early life factors for the aging processes.

In our understanding of health in old age, these developments call for a renewed focus on the early prevention of age-associated declines in health and the promotion of healthy aging at the population level. Consequently, we decided to develop a midlife biobank and database with a primary focus on biological, psychological, and social variables to study aging processes across the entire life course. The Copenhagen Aging and Midlife Biobank (CAMB) study has been established to supplement existing studies with par-ticular emphasis on early-life exposures in aging processes and to contribute important new information on the life-course determinants of late-life health. The CAMB study will be uniquely suited to accomplish this goal, because



Avlund et al. 7

(a) it is based on three existing cohorts with a variety of early life biological, psychological, and social variables; (b) it includes a large and reasonably representative sample of men and women in late midlife; (c) it includes com-prehensive life-course assessments of well-established and novel risk factors, which are hypothesized to contribute to age-associated declines in health, including cognitive ability measured in childhood and early adulthood, work life factors (e.g., work history), life events and stressful social relations; (d) it includes a number of biological and psychological indicators of early aging not available in other studies (e.g., detailed measures of low-grade inflamma-tion, vigorous physical function, and fatigue); (e) it incorporates the possibil-ity of complete register-based follow-up using the many national Danish medical and socioeconomic registers; (f) in comparison with studies in other countries, it will make it possible to evaluate the influence of the public Danish social security and health service system on trajectories of aging and on associations between early life factors and health outcomes; and (g) it will establish a research infrastructure, and facilitate a variety of mechanistic studies, which will provide a more detailed understanding of the biological processes through which early-life social and behavioral exposures and risk factors express themselves in health outcomes and trajectories in late life. Thus, CAMB is expected to add significant contributions to existing life-course studies in other countries.

The exposures included in the CAMB data collection were selected based on prior indications of their potential relevance for relevant aging processes and outcomes. They include questionnaire data on social, psychosocial, and labor market circumstances, such as stressful social relations and work life history. In addition, a number of social and psychological exposures were measured several times in participants prior to the CAMB study, for example, perceived stress, depression, work-ability, and health behavior. Consequently, prospective data are available, and the repeated measurements in CAMB make it possible to analyze changes in both exposure states and outcome variables.

Some early signs of the aging process do not present themselves initially as a disease or a pathological condition, but may manifest themselves as decreased muscle strength (Cooper et al., 2011), fatigue (Avlund, 2010), or low-grade inflammation (Krabbe, Pedersen, & Bruunsgaard, 2004). Nevertheless, these signs may reflect increased vulnerability in biologic and physiologic systems and several of these indicators have been predictive of adverse health outcomes. There are large individual differences in the time of occurrence of these signs. However, little is known about factors which influ-ence early aging signs in late midlife. Thus, the variables in CAMB were selected to include signs of early aging in midlife as well as a wide range of




exposures that potentially influence aging-related processes. Relevant mark-ers of early aging were selected according to the number of criteria: They should reflect early signs of aging, defined as markers of aging in individuals compared to age peers; they should show sufficient variability among indi-viduals in late midlife; and they should be amenable to efficient data collec-tion in the context of an epidemiological study.

Study Design

CAMB is based on a merger of three established cohorts, two of which have been followed since birth: The Metropolit Cohort (MP; 10,171 men born in Copenhagen in 1953, age at follow-up 56-58), The Copenhagen Perinatal Cohort (CPC; 8,102 men and women born at the National University Hospital in Copenhagen in 1959-1961, age at follow-up 49-52), and the Danish Longitudinal Study on Work, Unemployment, and Health (DALWUH; 11,082 men and women, born 1949 and 1959, constituting a random sample of the Danish population in 1999, age at follow-up 50-53 and 60-63). Each of the cohorts has unique assets. The MP cohort (Osler, Lund, Kriegbaum, Christensen, & Nybo Andersen, 2006) has excellent data on cognitive ability and socioeconomic factors in childhood and early adulthood, but is limited to men born in Copenhagen Metropolitan Region. The CPC cohort (Zachau-Christiansen, 1972) has very detailed data about prenatal, perinatal, and early postnatal conditions, but is limited to individuals born at the National University Hospital in Copenhagen. The DALWUH (U. Christensen et al., 2004) is linked up to registers with data back to early adulthood, has excellent data on a range of psychosocial factors, and is representative of the Danish population in the included age groups. Table 1 shows a summary of available data collected in previous studies of the three original cohorts as well as in the newly merged CAMB cohort.

Participants in the CAMB cohort belong to the post-World War II baby boom population. They grew up in the 1950s and 1960s and although some were exposed to postwar economic and material restrictions in the 1950s, they experienced the economic boom in the 60s. They were children or young adults in the late 60s with student revolt, hippie movement, drug experimen-tation, and women’s movement. The birth-control pill was permitted by law in 1966, and free abortions before Week 12 became legal for all Danish women in 1973. Nearly all female CAMB participants still are—or have been—active on the labor market. The CAMB data provide unique opportu-nities to study how changes, reflecting the development of contemporary society, influenced the health of a whole generation.

The original three cohorts included a total of 29,355 individuals. These can all be followed by register linking to health- and mortality registers.



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Table 1. Summary of Data Collected in the Three Cohorts and in CAMB.

MP CPC DALWUH CAMB

born 1953 (n = 7,987)

born 1959-1961 (n = 9,125)

born 1949 and 1959 (n = 7,598)

2009-2011 (n = 7,191)

Parents SEP SEP SEP Height Grandparents SEP Early life Pregnancy data — 1959-1961 — Birth weight and length 1953 1959-1961 — Duration of birth 1953 1959-1961 — Child’s development — 1959-1961 and

1960-1962—

Family relations — 1960-1962 — Early adolescence Cognitive tests 1965-1966 — — Social factors 1965-1966

and 1968— —

Family structure 1968 — — Anthropometry 1968 — — Early adult life Own SEP 1971 1988-1990 — Anthropometry 1971 1988-1990 — Cognitive tests 1971 1978-1982 — Diseases 1971 1988-1990 — Adult life Sociodemographic factors 2004 1982-1994 and

20022000 and 2006 2009-2011

Social relations 2004 1982-1994 2000 and 2006 2009-2011Physical health Anthropometry 2004 1982-1994 and

20022000 and 2006 2009-2011

Blood pressure — 2002 — 2009-2011 Long-standing illness 2004 1982-1994 and

20022000 and 2006 2009-2011

Reproductive history 2004 1982-1994 2000 and 2006 2009-2011 Muscle performance — — — 2009-2011 Lung function — — — 2009-2011 Functional limitations 2004 — — 2009-2011 Physical performance 2004 — — 2009-2011 Fatigue 2004 — — 2009-2011 Self-rated health 2004 — 2000 and 2006 2009-2011 Medication use — 1982-1994 and

20022006 2009-2011

Oral health 2004 — — 2009-2011Mental health Cognitive function — 1982-1994 — 2009-2011 Depressive mood 2004 1982-1994 2000 and 2006 2009-2011 Life satisfaction — 1982-1994 2006 2009-2011 Perceived stress — — 2000 and 2006 2009-2011

(continued)




When these cohorts were merged, 4,604 individuals had died or had previ-ously asked to be excluded from cohort follow-ups. This left 24,751 persons eligible for invitation into CAMB. Due to resource restrictions, we further had to exclude 6,814 persons (28% of those eligible) as they lived in the Western part of Denmark, too far from the study clinic. Thus, 17,937 persons were invited to participate in CAMB. The selected cohort members were sent an invitation letter by regular mail including information about the study and a comprehensive questionnaire. Participants in the data collection received further information about the study, and informed consent forms were handed out if a cohort member agreed to participate. By signing the informed con-sent, participants agreed to the storage of blood samples in a research biobank for future research projects and to linkage of their data with social and health registries. Participants were also informed that they can choose to withdraw from the study at any time, and/or they can ask to get their data from the questionnaire, tests, and biological samples destroyed. The participants were notified of clinically important findings after the examination day, if rele-vant, unless they had specifically asked not to receive them.

Reminders were mailed 4 weeks after the first invitation. At the end of the data collection period, a final reminder was sent to those who had not responded to any of the previous letters. The local ethical committee has approved the CAMB as a database combining the three cohorts (No: H-A-2008-126). CAMB has also been registered at the Danish Data Protection Agency as a combined database (No: 2008-41-2938).

MP CPC DALWUH CAMB

born 1953 (n = 7,987)

born 1959-1961 (n = 9,125)

born 1949 and 1959 (n = 7,598)

2009-2011 (n = 7,191)

Stressful life events — — 2006 2009-2011 Hostility 2004 — 2000 and 2006 2009-2011 Personality traits — 1982-1994 — Health-related behavior 2004 1982-1994 2000 and 2006 2009-2011 Physical activity Smoking Dietary characteristics Alcohol consumption Indoor air quality — — — 2009-2011 Inflammatory markers — — — 2009-2011 Other blood measures — — — 2009-2011

Note. CAMB = Copenhagen Aging and Midlife Biobank; MP = The Metropolit Cohort; CPC = The Copen-hagen Perinatal Cohort; DALWUH = The Danish Longitudinal Study on Work, Unemployment, and Health; SEP = Socioeconomic position.

Table 1. (continued)



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A total of 7,190 participants (40%) completed the questionnaires, and 5,575 participants (31%) came to a study clinic for further testing and a blood draw. We have compared participants and non-participants by linking the CAMB data set to national registries. Compared to non-participants, CAMB participants did not differ substantially with regard to educational level. However, a larger proportion of participants were employed compared with non-participants, suggesting that CAMB study participants represent a some-what socially selected group. In addition, we used the number of contacts with general practitioners as a health measure for the non-response analysis, because referral from a general practitioner is needed for all non-acute medi-cal examinations and treatment at hospitals, and visits to specialists and phys-ical therapists. Number of contacts with general practitioner during the year 2009 was nearly the same for participants and non-participants, suggesting that the two groups are likely to be comparable in overall health.

Data collection took place at The National Research Centre for the Working Environment from 2009 to 2011. The visit to the study clinic included an interview on current illnesses and use of medication (n = 5,575), blood tests, basic examination (height, weight, percentage of body fat, blood pressure), muscle tests (handgrip [n = 5,558], trunk [n = 4,641], back muscle strength [n = 4,595], muscle power [n = 4,763]), lung function (spirometry; n = 5,546), balance (n = 5,347), flexibility (n = 4,917), reaction time (n = 5,564), and chair rise (n = 5,046; Hansen, Lund, et al., 2014). Submaximal oxygen uptake (n = 1,496), muscle fatigue (n = 965), and oral health (n = 1,518) were measured in subsets of the cohort. Cognitive ability was assessed using the Intelligenz-Struktur-Test (I-S-T 200R; n = 5,557), which primarily measures verbal fluency functions (Mortensen, Flensborg-Madsen, Molbo, Fagerlund, et al., 2014).

The questionnaire (n = 7,190) included questions about health, use of medica-tions, early signs of mobility disability (Melzer, Lan, & Guralnik, 2003), fatigue (e.g., Multiple Fatigue Inventory-20; Smets, Garssen, Bonke, & De Haes, 1995), self-assessed physical fitness (Strøyer et al., 2007), stress (Pejtersen, Kristensen, Borg, & Bjorner, 2010), life satisfaction (Diener, Emmons, Larsen, & Grimmins, 1985), occupational social class (U. Christensen et al., 2014), work ability, work life history, social relations (Lund et al., 2014), social capital, health behavior, sleep, life events, and indoor air quality. Measures of mental health included questions on depression (Major Depression Inventory; Olsen, Jensen, Noerholm, Martiny, & Bech, 2003), hostility (Cynical Distrust Scale; U. Christensen et al., 2004), personality (Neuroticism-Extroversion-Openness Five-Factor-Inventory SCL-90: Symptom Check List 90 [NEO-FFI]; Mortensen, Flensborg-Madsen, Molbo, Christensen, et al., 2014), and mental distress and symptoms (Symptom Check List 90 [SCL-90]; Derogatis, 2007).




Non-fasting blood samples were collected by trained laboratory techni-cians, and analyses were conducted immediately on cholesterol, glucose, and hemoglobin using fresh blood, before they were frozen. Plasma, serum, and DNA were isolated and stored at −80°C. After the data collection, we ana-lyzed HbA1c, fractioned lipid profile, circulating levels of several inflamma-tory markers, including high sensitivity C-reactive protein (hsCRP), TNF-α, IL-1β, IL-18, IL-6, IFN-γ, and IL-10. In addition, levels of IL-1 autoantibod-ies have been measured. The remaining samples of plasma, serum, and DNA are stored in a research biobank for future studies.

Because all blood samples were collected at one facility, it was possible to collect and store samples in a completely standardized way to ensure stan-dardized handling, optimal storage, and high sample quality. Our standard operating procedures were based on the advice from a range of established biobanks in Denmark, members of the European biobank network European, Middle Eastern and African Society for Biopreservation and Biobanking (ESBB), and the Organisation for Economic Co-operation and Development (OECD) Best Practice Guidelines for Biological Resource Centres–2007. Standard operating procedures are available on request.

After collection of the blood samples, they were kept at room temperature for 2 hr before separating fractions, pipetting into 1 ml aliquots and initial freezing. This short handling time ensures minimal loss of biologically rele-vant compounds over the longest foreseeable storage time. Our barcode labeled cryotubes are stored at −80°C in a temperature monitored freezer and tracked using freezer steering software (Freezerworks Unlimited, Dataworks Development, Inc). This ensures the safety and traceability of each sample.

After data from the different sources were cleaned for errors, they were formatted and linked, and the data collection process was documented. Participants are identified by a unique participation number, securing ano-nymity and correct linking of data from all sources, and correct linkage of the CAMB database to national registers. Several of the questions had to be re-coded according to national and international rules by experienced coders; for example, occupational social class, occupation (Danish version of the International Standard Classification of Occupations (DISCO) codes), and use of prescribed medicines by the Anatomical Therapeutic Chemical (ATC) codes.

Table 2 provides basic characteristics of the study sample by gender. About two thirds are men, owing to the fact that one of the three constituent cohorts, the Metropolit Study, is all male. The age range is 49 to 53 and 56 to 63 years, with the majority being in the older age group. About 80% are still in regular employment, and 21% live alone. The vast majority (98%) is of Danish origin; the remainders are from other European countries (1%) and



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Table 2. Sociodemographic and Health Characteristics of the CAMB Study Population by Gender.

Men % (n = 4,996)

Women % (n = 2,249)

Total % (n = 7,245)

Sociodemographic factors Age at CAMB baseline examination 49-53 27 75 42 56-63 73 25 58 Danish origin 99 97 98 Main occupation Full-time employee (more than

30 hours weekly)68 65 67

Part-time employee, self-employed 15 14 15 Unemployed 11 17 13 Other (flex job, work training, pension) 6 4 6 Live alone 20 24 21Healtha

Excellent/very good/good self-rated health

87 87 87

Have or have had one of the following diseases Asthma 9 11 10 Chronic obstructive pulmonary disease 6 5 5 Diabetes 6 3 5 Arthritis 22 26 23 Functional limitationsa

Difficulty walking 400 m without resting

10 10 10

Limited in running 100 m 29 33 30 Limited in climbing stairs to the second

floor17 22 18

Body mass index (kg/m2)b

<18.5 1 2 1 18.5 to 24.9 36 52 41 25 to <30 45 30 41 30+ 16 14 15Health-related behaviora

Daily smokers 27 25 26 Physical activity less than 4 hours

per week37 28 34

Weekly alcohol consumption above recommendations Men:>21/

women:>1421 12 18

Daily intake of fruits or vegetables 33 55 40

Note. CAMB = Copenhagen Aging and Midlife Biobank.aData from the questionnaire.bData from the physical examination.




from other parts of the world (1%). More than 85% rate their health as excel-lent, very good, or good. Approximately 10% have been diagnosed with asthma, 6% have chronic obstructive pulmonary disease (COPD), 6% have diabetes, and about one fourth has arthritis. About 10% to 30% report some kind of functional limitation. Regarding health-related behaviors, 26% are daily smokers, 34% are physically active less than 4 hr per week, 18% drink alcohol above the recommended limits, and 20% do not eat fruits or vegeta-bles at a daily basis. Furthermore, more than 40% are overweight and 15% are obese. These results are similar to results among men and women in approximately the same age group based on a survey from the Danish National Board of Health in 2010 (A. I. Christensen et al., 2011).

An important advantage of epidemiologic research in Denmark is that this country offers efficient access to high-quality databases (Frank, 2003) as well as access to a range of medical and social administrative national data regis-tries. This provides a unique possibility of linking data from national regis-ters to each CAMB participant via the Central Person Registration (CPR) number, which is assigned to all persons with a permanent residence in Denmark. The available register information includes complete registration of all hospital admissions and diagnoses as well as information on social and economic factors, such as income and social benefits.

Table 3 provides an overview of the registers and available information from these data sources. Information is available for each year for all indi-vidual CAMB participants independent of whether he or she participated. As shown in Figure 1, information on social and demographic factors, such as marital status and family relations from the CPR register, are available from the time when the youngest (born 1962) and oldest (born 1949) cohort mem-bers were 6 and 19 years old, respectively, while information on prescription medication from the most recently established National Drug Prescription register can be retrieved from 33 to 46 years for these birth cohorts. This makes it possible to study whether changes over the life course in social rela-tions, socioeconomic position, or use of prescription medication influence health later in life. Furthermore, it allows us to study social consequences of chronic disease such as the probability of receiving social benefits after inci-dent diabetes or heart disease.

CAMB is managed by a steering committee, which is responsible for grant applications, data collection, the establishment of CAMB as an aggregate, all-inclusive database, and for optimal use of the data. The steering committee is composed of researchers from the University of Copenhagen (Department of Public Health and Department of Odontology), Copenhagen University Hospital (Centre for Inflammation and Metabolism), Glostrup University Hospital (Research Centre for Prevention and Health), and the National



Avlund et al. 15

Table 3. Register-Based Linkages Planned or Available for the 17,937 Members of the CAMB.

Start of registration Register Information

1.4.1968- Danish Civil Registration System

Vital status, marital status history, family relations (date of birth and vital status for parents and biological children)

1.4.1968- The Cause of Death Register

Causes of death based upon the death certificates. Coded using seventh revision of ICD for 1958-1968; eighth revision for 1969-1993 and 10th revision for 1994-1998.

1.1.1978- The National Patients Register

Time of admission to somatic hospitals, operations and diagnosis at discharge. Discharge diagnosis coded using eighth revision of ICD for 1977-1993 and tenth revision for 1994-2000.

1.1.1990- The National Health Services Register

Data from contractors in health services in primary health care

1.1.1994- The National Drug Prescription register

Dispensed prescription drugs

1.1.1970- The Danish Psychiatric Central Register

Time of admission to psychiatric hospitals and diagnosis at discharge. Discharge diagnosis coded using eighth revision of ICD for 1969-1993 and 10th revision for 1994-2003.

1.4.1968- The Danish Cancer Register

Time of cancer diagnosis. Coded using seventh revision of ICD.

1.1.1981- The Integrated Database for Labor Marked Research (IDA) in Statistics Denmark

Data from all companies with more than one employee, the taxation authorities, the registry relating to Unemployment, the Integrated Student Registry

1.7.1991 The Danish Register for Evaluation of Marginalization (DREAM) Register

Data on social benefits or any other transfer income since 1991

Note. CAMB = Copenhagen Aging and Midlife Biobank; ICD = International Classification of Disease.

Research Centre for the Working Environment. Individual members are from a broad range of disciplines, which ensures comprehensive and interdisciplin-ary use of the data: gerontology, medicine, public health, social epidemiology, immunology, odontology, pharmacy, psychology, and stress research.




The CAMB steering group welcomes any collaboration on research proj-ects using CAMB data. Researchers interested in using CAMB data should submit an application for permission to access to and use of data from CAMB, complete a standard collaboration form, and enclose a research proposal. Researchers will get access to CAMB data when their application has been approved by the steering committee and the collaboration agreement has been signed by both parties. Data will be handed over and treated according to terms decided by the Danish Data Protection Agency and other authorities. The Scientific Ethical Committee has approved the use of biological material from CAMB participants for research projects that investigate hemoglobin, HbA1c, cholesterol, and blood sugar as well as inflammatory and genetic markers of special importance for the aging process, including cytokines,

Figure 1. Data on exposure and confounders that can be obtained for participants and non-participants from the Metropolit Cohort (MC, blue lines), The Danish Longitudinal Study on Work, Unemployment and Health (DALWUH, red lines), and the Copenhagen Perinatal Cohort (CPC, green lines), which is the study population in the Copenhagen Aging and Midlife Biobank (CAMB) in relation to subcohort membership.



Avlund et al. 17

acute phase proteins, other proteins in blood, and polymorphisms in inflam-matory genes. Thus, such projects only need additional approval by the CAMB Steering Committee. The use of blood samples from CAMB for other purposes must be approved both by the CAMB steering committee and according to existing rules by the Danish Data Protection Agency and the Scientific Ethical Committee. When a project is completed, the data and the right to use biological materials will be transferred to CAMB, unless other rules have been agreed upon and stated in the collaboration agreement. For further details, see our website (www.camb.ku.dk).

Contents of the Issue

This special issue is composed of eight articles that detail the study design, the construction of social variables and tests, and basic empirical data for the study measures included in CAMB. We have included articles that use CAMB data to investigate several signs of early aging and important social exposures. Exposures were selected based on prior findings regarding their potential relevance for aging-related processes. A number of social expo-sures were measured several times prior to the CAMB data collection in the specific cohorts and were repeated in CAMB, making analyses of changes in exposure possible. This is the focus of the article by U. Christensen et al. (2014), which describes the theoretical background and coding of the Danish Occupational Social Class measure and relates it to three aging-related outcomes in midlife. In addition, the article by Lund et al. (2014) describes the content validity and reliability of the Copenhagen Social Relations Questionnaire (CSRQ). One article utilizes the CAMB data to investigate allostatic load (Hansen, Lund, et al., 2014) as a biological marker of early signs of aging in late midlife. Several articles focus on social gradients in outcomes: allostatic load (Hansen, Lund, et al., 2014), physical performance (Hansen, Andersen, et al., 2014), cognitive ability (Mortensen, Flensborg-Madsen, Molbo, Fagerlund, et al., 2014), and per-sonality traits (Mortensen, Flensborg-Madsen, Molbo, Christensen, et al., 2014). Finally, one article analyzes the importance of health-related behav-ior and health, such as effects of smoking and alcohol consumption on den-tal health (Morse et al., 2014).

Taken together, the CAMB database will provide excellent opportunities to examine relationships between a wide range of early life experiences, mid-dle-age risk factors and biomarkers, and late midlife signs of early aging. This special issue showcases an innovative longitudinal study on one of the least explored areas of aging, early signs of aging in late midlife, with the intention to encourage its use beyond the local team of investigators. The information included in CAMB will be of vital importance for developing




strategies to prevent age-associated declines in health and to promote healthy aging in future generations of older adults in Denmark and elsewhere. In addition, results based on CAMB may provide important knowledge on how to reduce and control the exponentially growing health care costs that coun-tries with aging populations will face during the coming decades.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Copenhagen Aging and midlife Biobank has been supported by a generous grant from the VELUX FOUNDATION.

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copenhagen aging and midlife biobank (camb): an introduction

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