Also the welfare state of Sweden has prominent socioeconomic (SES) differences in health. These are seen for most measures of SES, i e for education, occupation and income, and also for most health outcomes: for all-cause mortality, for morbidity in most diseases and for self-rated health. SES differences are, in particular, evident for coronary heart disease (CHD) with a two-fold difference in incidence and death between high and low SES groups. Causes for this are not clear. It is well known that an unhealthy lifestyle is more common in low SES but this can only explain a part of observed SES differences.

One possible explanation is effects of psychosocial factors. High levels of psychosocial risk factors and low availability of psychosocial resources are well documented predictors of CHD and more common in low SES. We and others have demonstrated that these factors are related to poor function of the HPA axis with reduced cortisol reactivity and with higher levels of markers for inflammation and plaque vulnerability, which also are known predictors of CHD.

The overall objective of the research program is to analyse, in a prospective design, to what extent socioeconomic differences in CHD incidence and death can be explained by psychosocial factors, especially psychological resources, and if observed effects are mediated by biological markers of stress, inflammation and plaque vulnerability.
Our data builds on two cohorts, using the same design of a random sample from a normal middle-aged Swedish population. Data collection: cohort I 2003-2004 (n=1007); cohort II 2012-2015 (n=2051), used a comprehensive design with broad questionnaires on SES, psychosocial risk factors, psychological resources, lifestyle and present disease, anthropometrics, saliva and blood samples. Primary outcome is symptomatic CHD. In a nested case control design data for cases shall be compared to controls.

While CHD incidence is falling, SES differences in CHD incidence and mortality remain and causes for this are not clear. This is one of few prospective studies linking the chain from SES, via psychosocial factors to biological markers of stress, inflammation and plaque vulnerability and CHD. The study has, therefore, the potential to generate important knowledge on causes behind SES disparities in CHD and on “how stress gets under your skin”
More information about study design, study populations and timeline is available in document under the tab Documentation.

Cohort 1: Data collection is conducted in collaboration with 10 Primary Health Care centers (PHCs) in Östergötland county council and sampling was done from the normal population of the catchment area for each PHC. The study is build on a comprehensive design with broad questionnaires on SES, psychosocial risk factors, psychological resources, lifestyle and present disease, anthropometrics, saliva and blood samples.

Cohort 2: Data collection is conducted in collaboration with 27 PHCs in Östergötland and 19 PHCs in Jönköping county council. The same methods are used for collecting data, as described for cohort 1. Show less..

Data contains personal data

Yes

Sensitive personal data

Yes

Type of personal data

Medical data

Code key exists

Yes

Method and outcome

Unit of analysis

Individual

Time Method

Longitudinal

Sampling procedure

Probability

Random samples from the normal population.

Time period(s) investigated

2003-09-30 – 2004-03-03

2012-08-21 – 2015-12-31

Biobank is connected to the study

Yes

Number of individuals/objects

1007

Data format / data structure

Numeric

Data collection

Data collection 1

Mode of collection: Measurements and tests
Time period(s) for data collection: 2003-09-30 – 2004-03-03
Data collector: Linköping University, Department of Medical and Health Sciences
Number of responses: 1007
Source of the data: Population group

Data collection 2

Mode of collection: Self-administered questionnaire
Time period(s) for data collection: 2003-09-30 – 2004-03-03
Data collector: Linköping University, Department of Medical and Health Sciences
Number of responses: 1007
Source of the data: Population group

Data collection 3

Mode of collection: Self-administered questionnaire
Time period(s) for data collection: 2012-08-21 – 2015-12-31
Data collector: Linköping University, Department of Medical and Health Sciences
Number of responses: 7051
Source of the data: Population group

Data collection 1

Mode of collection: Measurements and tests
Time period(s) for data collection: 2003-09-30 – 2004-03-03
Data collector: Linköping University, Department of Medical and Health Sciences
Number of responses: 1007
Source of the data: Population group

Data collection 2

Mode of collection: Self-administered questionnaire
Time period(s) for data collection: 2003-09-30 – 2004-03-03
Data collector: Linköping University, Department of Medical and Health Sciences
Number of responses: 1007
Source of the data: Population group

Data collection 3

Mode of collection: Self-administered questionnaire
Time period(s) for data collection: 2012-08-21 – 2015-12-31
Data collector: Linköping University, Department of Medical and Health Sciences
Number of responses: 7051
Source of the data: Population group

Data collection 4

Mode of collection: Measurements and tests
Time period(s) for data collection: 2012-08-21 – 2015-12-31
Data collector: Linköping University, Department of Medical and Health Sciences
Number of responses: 7051
Source of the data: Population group

Show less..

Geographic coverage

Geographic spread

Geographic location: Sweden, Östergötland County, Jönköping County

Administrative information

Responsible department/unit

Department of Medical and Health Sciences

Ethics Review

Linköping - Ref. 02-324 and 2012/8031

Topic and keywords

Research area

Medical and health sciences (Standard för svensk indelning av forskningsämnen 2011)

Health (CESSDA Topic Classification)

Keywords

Socioeconomic factors, Inflammation, Cohorts.se, Stress, Psychosocial factors, Psychological resources

Publications

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Garvin, P., Jonasson, L., Nilsson, L., Falk, M., & Kristenson, M. (2015). Plasma Matrix Metalloproteinase-9 Levels Predict First-Time Coronary Heart Disease: An 8-Year Follow-Up of a Community-Based Middle Aged Population. In PLOS ONE (Vol. 10, Issue 9, pp. e0138290-). https://doi.org/10.1371/journal.pone.0138290
DOI: https://doi.org/10.1371/journal.pone.0138290
URN: urn:nbn:se:liu:diva-122112
SwePub: oai:DiVA.org:liu-122112

Garvin, P., Nilsson, E., Ernerudh, J., & Kristenson, M. (2015). The joint subclinical elevation of CRP and IL-6 is associated with lower health-related quality of life in comparison with no elevation or elevation of only one of the biomarkers. In Quality of Life Research (Vol. 25, Issue 1, pp. 213–221). https://doi.org/10.1007/s11136-015-1068-6
URN: urn:nbn:se:liu:diva-124641
DOI: https://doi.org/10.1007/s11136-015-1068-6
SwePub: oai:DiVA.org:liu-124641

Granström, F., Molarius, A., Garvin, P., Elo, S., Feldman, I., & Kristenson, M. (2015). Exploring trends in and determinants of educational inequalities in self-rated health. In Scandinavian Journal of Public Health (Vol. 43, Issue 7, pp. 677–686). https://doi.org/10.1177/1403494815592271
URN: urn:nbn:se:liu:diva-122099
DOI: https://doi.org/10.1177/1403494815592271
SwePub: oai:DiVA.org:liu-122099

Pössel, P., Mitchell, A. M., Sjögren, E., & Kristenson, M. (2015). Do Depressive Symptoms Mediate the Relationship Between Hopelessness and Diurnal Cortisol Rhythm? In International Journal of Behavioral Medicine (Vol. 22, Issue 2, pp. 251–257). https://doi.org/10.1007/s12529-014-9422-6
DOI: https://doi.org/10.1007/s12529-014-9422-6
URN: urn:nbn:se:liu:diva-115573
SwePub: oai:DiVA.org:liu-115573

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