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High North Population Studies (BiN)


Image caption Photo: Yngve Olsen Sæbbe

High North Population Studies (BiN) is an interdisciplinary strategic initiative at UiT The Arctic University of Norway aimed to provide scientific knowledge about the populations health and living conditions in the High North. We also aim to support knowledge-based health policy decision-making to improve the quality of health planning and healthcare in the High North.

Project period: 01.01.2018 - 31.12.2021

BiN consists of six research and focus areas:

  • Technology
  • Lifestyle and health
  • Social inequality in health
  • Youth health
  • Pollutants
  • Data sources for research

The initiative is anchored in the university's strategy "Driving Force in the North" and the knowledge area of health, welfare, and quality of life, with particular emphasis on public health, disease control, and living conditions at all stages of life. Furthermore, the initiative is anchored in the UN Sustainable Development Goals.

BiN also had a stated goal to develop research collaboration across disciplines and faculties and was a joint effort between five faculties, UiT level 1, and Northern Norway Regional Health Authority. The project had its own steering group, project leader, a leadership group, and project coordinator.

The total initiative included 5 postdoctoral and 11 PhD positions. During the project, several other PhD positions were added to the research and focus areas.

The majority of BiN's PhD fellows have supervisors from more than one faculty. While 8 PhD fellows have defended their theses, another 11 are in process, and the last defense is expected in 2025. At the project's end in December 2021, the project had published 49 articles in peer-reviewed journals. Several research projects related to the focus areas of Lifestyle and Health, Social Inequality in Health, an Data sources for research
are being continued in the project Healthy Choices. The majority of ongoing PhD fellows are also followed up within the framework of the Healthy Choices initiative.

Link to BiN web site

Members from Epidemiology of chronic diseases research group (KSE)

Torbjørn Wisløff
Laila Arnesdatter Hopstock
Sameline Grimsgaard
Anne Elise Eggen
Inger Njølstad
Anne-Sofie Furberg
Bente Morseth
Maria Averina
Jonas Johansson, Postdoktor in BiN
Andre Henriksen, PhD in BiN
Monika Machlik, PhD in BiN
Nils Abel Aars, PhD in BiN
Dina Stensen, PhD in BiN
Chi Quynh Vo, PhD in BiN

Publications with authors from KSE
  1. Aars NA, Jacobsen BK, Morseth B, Emaus N, Grimsgaard S. Longitudinal changes in body composition and waist circumference by self-reported levels of physical activity in leisure among adolescents: the Tromsø study, Fit Futures. BMC Sports Sci Med Rehabil 2019;11:37.
  2. Aars NA, Beldo S, Jacobsen BK, Horsch A, Morseth B, Emaus N, Furberg AS, Grimsgaard S. Association between objectively measured physical activity and longitudinal changes in body composition in adolescents: the Tromsø study fit futures cohort. BMJ Open 2020;10:e036991.
  3. Averina M, Brox J, Huber S, Furberg AS. Perfluoroalkyl substances in adolescents in northern Norway: Lifestyle and dietary predictors. The Tromsø study, Fit Futures 1. Environment International 2018;114:123-130.
  4. Averina M, Brox J, Huber S, Furberg AS, Sørensen M. Serum perfluoroalkyl substances (PFAS) and risk of various allergies in adolescents. The Tromsø study Fit Futures in Northern Norway. Environmental Research 2019;169:114-121.
  5. Averina M, Hervig T, Huber S, Kjær M, Kristoffersen EK, Bolann BJ. Environmental pollutants in blood donors: The multicentre Norwegian donor study. Transfusion Medicine 2020;30:201-209.
  6. Averina M, Brox J, Huber S, Furberg AS. Exposure to perfluoroalkyl substances (PFAS) and dyslipidemia, hypertension and obesity in adolescents. The Fit Futures study. Environmental Research 2021;195.
  7. Beldo SK, Morseth B, Christoffersen T, Halvorsen PA, Hansen BH, Furberg AS, Ekelund U, Horsch A. Prevalence of accelerometer-measured physical activity in adolescents in Fit Futures - part of the Tromso Study. BMC Public Health. 2020;20:1127.
  8. Charles D, Berg V, Nøst TH, Bergdahl IA, Huber S, Ayotte P, Wilsgaard T, Averina M, Sandanger TM, Rylander C. Longitudinal changes in concentrations of persistent organic pollutants (1986–2016) and their associations with type 2 diabetes mellitus. Environmental Research 2021;204, Part B 112129.
  9. Henriksen A, Haugen Mikalsen M, Woldaregay AZ, Muzny M, Hartvigsen G, Hopstock LA, Grimsgaard S. Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables. J Med Internet Res. 2018;20:e110.
  10. Henriksen A, Grimsgaard S, Horsch A, Hartvigsen G, Hopstock L. Validity of the Polar M430 Activity Monitor in Free-Living Conditions: Validation Study. JMIR Form Res 2019;3(3):e14438.
  11. Henriksen A, Sand AS, Deraas T, Grimsgaard S, Hartvigsen G, Hopstock L. Succeeding with prolonged usage of consumer-based activity trackers in clinical studies: a mixed methods approach. BMC Public Health. 2020;20:1300.
  12. Henriksen A, Johansson J, Hartvigsen G, Grimsgaard S, Hopstock L. Measuring physical activity using triaxial wrist worn Polar activity trackers: A Systematic review. Int J Exercise Science 2020;13: 438-454.
  13. Henriksen A, Johannessen E, Hartvigsen G, Grimsgaard S, Hopstock LA. Consumer-Based Activity Trackers as a Tool for Physical Activity Monitoring in Epidemiological Studies During the COVID-19 Pandemic: Development and Usability Study. JMIR Public Health Surveill. 2021;7:e23806.
  14. Huber S, Averina M, Brox J. Automated sample preparation and GC-API- MS/MS as a powerful tool for analysis of legacy POPs in human serum and plasma. Analytical Methods 2020;7: 912-929.
  15. Schistad EI, Kong XY, Furberg AS, Bäckryd E, Grimnes, Emaus N, Rosseland LA, Gordh T, Stubhaug A, Engdahl B, Halvorsen B, Nielsen CS. A population-based study of inflammatory mechanisms and pain sensitivity. Pain. 2020;161(2):338-350.
  16. Muzny M, Henriksen A, Giordanengo A, Muzik J, Grøttland A, Blixgård H, Hartvigsen G, Årsand E. Wearable sensors with possibilities for data exchange: Analyzing status and needs of different actors in mobile health monitoring systems. Int J Med Inform 2020;133:1-8.
  17. Nilsen L, Hopstock LA, Skeie G, Grimsgaard S, Lundblad MW. The Educational Gradient in Intake of Energy and Macronutrients in the General Adult and Elderly Population: The Tromsø Study 2015-2016. Nutrients. 2021;13:405.
  18. Nilsen L, Hopstock LA, Grimsgaard S, Carlsen MH, Lundblad MW. Intake of Vegetables, Fruits and Berries and Compliance to "Five-a-Day" in a General Norwegian Population-The Tromsø Study 2015-2016. Nutrients. 2021;13:2456.
  19. Nilsen OA, Ahmed LA, Winther A, Christoffersen T, Thrane G, Evensen E, Furberg AS, Grimnes G, Dennison E, Emaus N. Body Weight and Body Mass Index Influence Bone Mineral Density in Late Adolescence in a Two-Year Follow-Up Study. The Tromsø Study: Fit Futures. JBMR Plus. 2019;3:e10195.
  20. Nilsen OA, Emaus N, Christoffersen T, Winther A, Evensen E, Thrane G, Furberg AS, Grimnes G, Ahmed LA. The influence of snuff and smoking on bone accretion in late adolescence. The Tromso study, Fit Futures. Arch Osteoporos. 2021;16:143.
  21. Opdal IM, Morseth B, Handegård BH, Lillevoll K, Ask H, Nielsen CS, Horsch A, Furberg AS, Rosenbaum S, Rognmo K. Change in physical activity is not associated with change in mental distress among adolescents: the Tromsø study: Fit Futures. BMC Public Health. 2019;19:916.
  22. Opdal IM, Morseth B, Handegård BH, Lillevoll KR, Nilsen W, Nielsen C, Furberg AS, Rosenbaum S, Rognmo K. Is change in mental distress among adolescents predicted by sedentary behaviour or screen time? Results from the longitudinal population study The Tromso Study: Fit Futures. BMJ Open. 2020;10:e035549.
  23. Sagelv EH, Hopstock LA, Johansson J, Hansen BH, Brage S, Horsch A, Ekelund U, Morseth B. Criterion validity of two physical activity and one sedentary time questionnaire against accelerometry in a large cohort of adults and older adults. BMJ Open Sport Exerc Med. 2020;6:e000661.
  24. Sagelv EH, Ekelund U, Hopstock LA, Aars NA, Fimland MS, Jacobsen BK, Løvsletten O, Wilsgaard T, Morseth B. Do declines in occupational physical activity contribute to population gains in body mass index? Tromsø Study 1974-2016. Occup Environ Med. 2020:oemed-2020-106874.
  25. Sagelv EH, Ekelund U, Pedersen S, Brage S, Hansen BH, Johansson J, Grimsgaard S, Nordström A, Horsch A, Hopstock LA, Morseth B. Physical activity levels in adults and elderly from triaxial and uniaxial accelerometry. The Tromsø Study. PLoS One. 2019;14:e0225670.
  26. Sagelv EH, Ekelund U, Hopstock LA, Fimland MS, Løvsletten O, Wilsgaard T, Morseth B. The bidirectional associations between leisure time physical activity change and body mass index gain. The Tromsø Study 1974-2016. Int J Obes. 2021;45:1830-1843.
  27. Sari E, Moilanen M, Bambra C, Grimsgaard S, Njølstad I. Association between neighborhood health behaviors and body-mass index in Northern Norway: Evidence from the Tromsø Study. Scand J Public Health 2023;51:976-985. 
  28. Stangvaltaite-Mouhat L, Furberg AS, Drachev SN, Trovik TA. Common social determinants for overweight and obesity, and dental caries among adolescents in Northern Norway: a cross-sectional study from the Tromso Study Fit Futures cohort. BMC Oral Health. 2021;21:53.
  29. Stensen DB, Småbrekke L, Olsen K, Grimnes G, Nielsen CS, Simonsen GS, Sollid JUE, Furberg AS. Hormonal contraceptive use and Staphylococcus aureus nasal and throat carriage in a Norwegian youth population. PLoS One. 2019;14:e0218511.
  30. Stensen DB, Småbrekke L, Olsen K, Grimnes G, Nielsen CS, Sollid JUE, Simonsen GS, Almås B, Furberg AS. Circulating sex-steroids and Staphylococcus aureus nasal carriage in a general female population. Eur J Endocrinol. 2021;184:337-346.
  31. Syed S, Morseth B, Hopstock LA, Horsch A. Evaluating the performance of raw and epoch non-wear algorithms using multiple accelerometers and electrocardiogram recordings. Sci Rep. 2020;10:5866.
  32. Syed S, Morseth B, Hopstock LA, Horsch A. A novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks. Sci Rep. 2021;11:8832.
  33. Woldaregay AZ, Henriksen A, Issom DZ, Pfuhl G, Sato K, Richard A, Lovis C, Årsand E, Rochat J, Hartvigsen G. User Expectations and Willingness to Share Self-collected Health Data. Stud Health Technol Inform. 2020;270:894-898.