Joint Programming Initiative

More Years, Better Lives

The Potential and Challenges of Demographic Change

SMC, Swedish Mammography Cohort
SMC – Svensk Mammografi Cohort

Topic
Health and Performance
Wellbeing
Relevance for this Topic
Country Sweden
URL
More Topics

Governance

Contact information

Professor Alicja Wolk
Karolinska Institutet, Institute of Environmental Medicine, IMM
Nobels väg 13
171 77 Stockholm
Sweden
Phone: +46 8 524 861 70
Email: Alicja.Wolk(at)ki.se
Url: http://ki.se/ki/jsp/polopoly.jsp?d=40981

Timeliness, transparency

First publication regarding women from the Swedish Mammography Cohort, SMC was published year 1995. Time between collection of data and publication of results varies due to kind of research design, but takes approximately one year.

Type of data


Registry + Survey

Type of Study

Longitude survey: long-term study of the same sample

Cohort study

Data gathering method

Telephone interview (CATI)

Registries

Self-administered questionnaire


Cognitive tests Saliva, blood, urine, fat biopsies

Type of data


Registry + Survey

Type of Study

Longitude survey: long-term study of the same sample

Cohort study

Data gathering method

Telephone interview (CATI)

Registries

Self-administered questionnaire


Cognitive tests Saliva, blood, urine, fat biopsies


Access to data


On site access, as well as downloadable files are available after agreement. Participants were informed that their data can be analysed abroad.

Conditions of access


The data can be available on request. Data can only be provided after ethical testing and approval by the Stockholm Ethical Review Board. Information of the study is available at the study website (above) or by contact with principal investigator. Institution’s agreement needed. There are scalable fees to access samples varying according to the investigator (e.g. national investigators, students, public/private institutions, Questionnaires can also be used by permission of principal investigator.


Up to 3 months


Aggregated tables or anonymised microdata (depending on type of collaboration)


SAS, STATA, Excel


Research data is available in Swedish and English. Basic questionnaries also available in English.

Access to data


On site access, as well as downloadable files are available after agreement. Participants were informed that their data can be analysed abroad.

Conditions of access


The data can be available on request. Data can only be provided after ethical testing and approval by the Stockholm Ethical Review Board. Information of the study is available at the study website (above) or by contact with principal investigator. Institution’s agreement needed. There are scalable fees to access samples varying according to the investigator (e.g. national investigators, students, public/private institutions, Questionnaires can also be used by permission of principal investigator.


Up to 3 months


Aggregated tables or anonymised microdata (depending on type of collaboration)


SAS, STATA, Excel


Research data is available in Swedish and English. Basic questionnaries also available in English.


Coverage


The SMC is a population-based cohort study established in central Sweden (Västmanland and Uppsala counties) and includes about 90,000 women born 1914-1948. Baseline data in the SMC study were collected in 1987. The cohort includes questionnaire-based information about demographic factors and modifiable lifestyle factors such as diet, physical activity, smoking, weight, use of dietary supplements, some drugs “over counter”, and alcohol. There is also information on some sociologic and work-related factors. Other self-reported information regarding wellbeing, different symptoms related to aging (not available in the Swedish health registries), social aspects, housing, longevity of parents etc., is also available in the SMC. The baseline questionnaire (wave 1) was carried out between 1987 and 1990 and had a sample size of 61,433 women. A second questionnaire (wave 2) was carried out in 1997 with a sample size of 39,227 women. The third wave was carried out in 2008 with a sample of 25,332 women. The fourth wave was in 2009 with a sample of 30,621 women. Biomaterial was collected between 2003 and 2008, and included a sample size of 5,330 women.


1987


Born 1914-1948, women, central Sweden (Västmanland and Uppsala counties)


All women living in two counties in central Sweden were invited to the study


Central Sweden (Västmanland and Uppsala counties)


Born 1914-1948, 40-74 years old at baseline


Geographical restriction: Västmanland and Uppsala counties


The data is based on self-reported answers regarding present occupational status (full-time work, part-time work, house-wife, retired, disability, pension and unemployed). Information about work status is also obtained by linkage to Statistics Sweden (LISA register). With the information from the cohort, we are able to investigate aging and specific major chronic diseases such as cancer (breast, colon, bladder, kidney, etc.), cardiovascular diseases, osteoporosis, diabetes, age-related cataracts, lower urinary tract symptoms (LUTS), obesity, etc. Follow-up of the cohort is accomplished through annual matching with national and regional registers with high completeness of diagnoses and population registers at the Statistic Sweden. In a random subsample of the SMC we have DEXA measurements of bone status from 5,022 women (worlds-unique size of such material with other prospective data) and biological samples (blood, urine, fat biopsis) from 5330 women. Saliva samples (DNA source) are available from additional 9,000 women.


Of a total of over 200 peer-reviewed SMC publications, we present 20 selected articles. • Åkesson et al. Cadmium and postmenopausal endometrial cancer. Cancer Res 2008;68:6435-41. • Berrington de Gonzalez et al .BMI and mortality among 1.46m adults. N Engl J Med 2010;363:2211-9. • Di Giuseppe et al. Alcohol intake and risk of rheumatoid arthritis. BMJ. 2012;345:e4230. • Friberg et al. Alcohol and risk of endometrial cancer. Canc Epid Biomark Prev 2009;18:355-8. • Genkinger et al. Iron and red meat to endometrial cancer risk. Am J Clin Nutr 2012;96:848-54. • Harris et al. Alcohol and mortality among women with invasive breast cancer. Br J Cancer 2012;106:592-5. • Harris et al. Selenium and breast cancer mortality. Breast Cancer Res Treat 2012;134:1269-77. • Harris et al. Coffee and black tea and breast cancer mortality. Br J Cancer 2012;107:874-8. • Larsson et al. Chocolate consumption and risk of stroke. J Am Coll Cardiol 2011;58:1828-9. • Larsson et al. Fish consumption and stroke in Swedish women. Am J Clin Nutr 2011;93:487-93. • Larsson et al. Folate intake and pancreatic cancer incidence. J Natl Cancer Inst 2006;98:407-13. • Larsson et al. Fruit and vegetable consumption to ovarian cancer. Br J Cancer 2004;90:2167-70 • Larsson et al. Long term aspirin use and colorectal cancer risk. Br J Cancer 2006;95:1277-9. • Larsson et al. Tea consumption and ovarian cancer risk. Arch Intern Med 2005;165:2863-86. • Larsson et al. Whole grain and risk of colorectal cancer. Br J Cancer 2005;128:1830-7 • Rautiainen et al. Antioxidant capacity of diet and heart failure. Am J Med 2013;126:494-500. • Rautiainen et al. Multivitamin use and myocardial infarction. Am J Clin Nutr 2010;92:1251-6. • Stackelberg et al. Obesity and abdominal aortic aneurysm. Br J Surg 2013;100:360-6. • Suzuki et al. Alcohol and postmenopausal breast cancer risk. J Natl Cancer Inst 2005;97:1601-8. • Wolk A et al. Long-term fatty fish and renal cell carcinoma incidence. JAMA 2006;296:1-6.

Coverage


The SMC is a population-based cohort study established in central Sweden (Västmanland and Uppsala counties) and includes about 90,000 women born 1914-1948. Baseline data in the SMC study were collected in 1987. The cohort includes questionnaire-based information about demographic factors and modifiable lifestyle factors such as diet, physical activity, smoking, weight, use of dietary supplements, some drugs “over counter”, and alcohol. There is also information on some sociologic and work-related factors. Other self-reported information regarding wellbeing, different symptoms related to aging (not available in the Swedish health registries), social aspects, housing, longevity of parents etc., is also available in the SMC. The baseline questionnaire (wave 1) was carried out between 1987 and 1990 and had a sample size of 61,433 women. A second questionnaire (wave 2) was carried out in 1997 with a sample size of 39,227 women. The third wave was carried out in 2008 with a sample of 25,332 women. The fourth wave was in 2009 with a sample of 30,621 women. Biomaterial was collected between 2003 and 2008, and included a sample size of 5,330 women.


1987


Born 1914-1948, women, central Sweden (Västmanland and Uppsala counties)


All women living in two counties in central Sweden were invited to the study


Central Sweden (Västmanland and Uppsala counties)


Born 1914-1948, 40-74 years old at baseline


Geographical restriction: Västmanland and Uppsala counties


The data is based on self-reported answers regarding present occupational status (full-time work, part-time work, house-wife, retired, disability, pension and unemployed). Information about work status is also obtained by linkage to Statistics Sweden (LISA register). With the information from the cohort, we are able to investigate aging and specific major chronic diseases such as cancer (breast, colon, bladder, kidney, etc.), cardiovascular diseases, osteoporosis, diabetes, age-related cataracts, lower urinary tract symptoms (LUTS), obesity, etc. Follow-up of the cohort is accomplished through annual matching with national and regional registers with high completeness of diagnoses and population registers at the Statistic Sweden. In a random subsample of the SMC we have DEXA measurements of bone status from 5,022 women (worlds-unique size of such material with other prospective data) and biological samples (blood, urine, fat biopsis) from 5330 women. Saliva samples (DNA source) are available from additional 9,000 women.


Of a total of over 200 peer-reviewed SMC publications, we present 20 selected articles. • Åkesson et al. Cadmium and postmenopausal endometrial cancer. Cancer Res 2008;68:6435-41. • Berrington de Gonzalez et al .BMI and mortality among 1.46m adults. N Engl J Med 2010;363:2211-9. • Di Giuseppe et al. Alcohol intake and risk of rheumatoid arthritis. BMJ. 2012;345:e4230. • Friberg et al. Alcohol and risk of endometrial cancer. Canc Epid Biomark Prev 2009;18:355-8. • Genkinger et al. Iron and red meat to endometrial cancer risk. Am J Clin Nutr 2012;96:848-54. • Harris et al. Alcohol and mortality among women with invasive breast cancer. Br J Cancer 2012;106:592-5. • Harris et al. Selenium and breast cancer mortality. Breast Cancer Res Treat 2012;134:1269-77. • Harris et al. Coffee and black tea and breast cancer mortality. Br J Cancer 2012;107:874-8. • Larsson et al. Chocolate consumption and risk of stroke. J Am Coll Cardiol 2011;58:1828-9. • Larsson et al. Fish consumption and stroke in Swedish women. Am J Clin Nutr 2011;93:487-93. • Larsson et al. Folate intake and pancreatic cancer incidence. J Natl Cancer Inst 2006;98:407-13. • Larsson et al. Fruit and vegetable consumption to ovarian cancer. Br J Cancer 2004;90:2167-70 • Larsson et al. Long term aspirin use and colorectal cancer risk. Br J Cancer 2006;95:1277-9. • Larsson et al. Tea consumption and ovarian cancer risk. Arch Intern Med 2005;165:2863-86. • Larsson et al. Whole grain and risk of colorectal cancer. Br J Cancer 2005;128:1830-7 • Rautiainen et al. Antioxidant capacity of diet and heart failure. Am J Med 2013;126:494-500. • Rautiainen et al. Multivitamin use and myocardial infarction. Am J Clin Nutr 2010;92:1251-6. • Stackelberg et al. Obesity and abdominal aortic aneurysm. Br J Surg 2013;100:360-6. • Suzuki et al. Alcohol and postmenopausal breast cancer risk. J Natl Cancer Inst 2005;97:1601-8. • Wolk A et al. Long-term fatty fish and renal cell carcinoma incidence. JAMA 2006;296:1-6.


Linkage


The dataset is linked to Statistics Sweden where work occupation classification (SSYK) is used, which is based on ISCO-88.


There is ID for these over 60,000 participating women, which gives us a possibility to link to Swedish registers; we are updating their health status annually.

Linkage


The dataset is linked to Statistics Sweden where work occupation classification (SSYK) is used, which is based on ISCO-88.


There is ID for these over 60,000 participating women, which gives us a possibility to link to Swedish registers; we are updating their health status annually.


Data quality


Among the 60,000 participants there is some missing information (partial lack of answers to some questions).


ICD codes for specific diseases are all translated into the newest version ICD 10.


Yes

Data quality


Among the 60,000 participants there is some missing information (partial lack of answers to some questions).


ICD codes for specific diseases are all translated into the newest version ICD 10.


Yes


Applicability


Strengths: The longitudinal design provides good opportunities to study public health, gender and life styles. The broad variety of variables contributes to analyses of diet, physical activity, medical history, age at menarche, history of oral contraceptive use, age at menopause, postmenopausal hormone use and lifestyle factors such as cigarette smoking history and use of dietary supplements. The SMC database will be extended with genetic information. This will facilitate studies of genetic susceptibility and of interplay/interactions between lifestyle factors and genes in the development of chronic diseases and aging. Weaknesses: We do not have biological samples from the whole cohort.

Applicability


Strengths: The longitudinal design provides good opportunities to study public health, gender and life styles. The broad variety of variables contributes to analyses of diet, physical activity, medical history, age at menarche, history of oral contraceptive use, age at menopause, postmenopausal hormone use and lifestyle factors such as cigarette smoking history and use of dietary supplements. The SMC database will be extended with genetic information. This will facilitate studies of genetic susceptibility and of interplay/interactions between lifestyle factors and genes in the development of chronic diseases and aging. Weaknesses: We do not have biological samples from the whole cohort.


  • The information about this dataset was compiled by the author:
  • Kenneth Abrahamsson
  • (see Partners)