Hoppa direkt till innehållet
printicon

Registerbaserad forskning om barndomen för livslång hälsa och välfärd

Forskningsprojekt Ett initiativ i nätverksformat som syftar till att stärka interdisciplinär registerforskning i Sverige.

”Registerbaserad forskning om barndomen för livslång hälsa och välfärd” är ett forskningsprogram som finansieras av Vetenskapsrådet (VR) via dess satsning på SIMSAM – ”Swedish Initiative for research on Microdata in the Social And Medical sciences”, ett initiativ i nätverksformat som syftar till att stärka interdisciplinär registerforskning i Sverige.

Projektöversikt

Projektperiod

2009-01-01 2013-12-31

Finansiering

Finansår , 2009, 2010, 2011, 2012, 2013

huvudman: Umeå universitet, finansiar: Vetenskapsrådet, y2009: 576, y2010: 576, y2011: 576, y2012: 576, y2013: 576,

Forskningsämne

Folkhälsovetenskap och samhällsmedicin

Projektbeskrivning

The Umeå SIMSAM Lab was established to perform high quality, interdisciplinary microdata research on childhood and its relationship with lifelong health and welfare, focusing on areas of societal importance (Figure 1). The Lab has an exceptional microdata infrastructure combining social and medical data, innovative methodology, and awareness of the need to make research results available for policy development.

Recent medical, social and economic trends suggest that living conditions and welfare will not inevitably improve for the generations ahead. Different sorting processes lead to people entering upon various life paths early on in life, and as an echo from the past, life opportunities are shaped by previous and current family circumstances alongside people’s aspirations, wishes and abilities.

Young generations in Sweden are brought up in one of the richest countries, with a political landscape favouring active income redistribution policies, and that has historically built up a welfare society designed to offer equal chances to develop talents and progress. Despite increased economic wealth, there are a variety of social problems and inequities that raise concerns for the future. With increasing proportions of children living in low-income families, the relative gap in resources between children in well-off and poor families is widening (Salonen, 2012). In Malmö, life expectancy varies by five years between different parts of the city. The report from the “Malmö commission” clearly documents the nature and extent of social problems and inequities in a Swedish context (Kommissionen för ett hållbart Malmö, 2013). Some of these problems may be attributed to administrative inability to coordinate and reallocate available resources for more efficient use. However, the failure to make necessary investments in children and adolescents based on their overall needs is a path that is neither economically nor socially sustainable (Irwin et al., 2007; CSDH, 2008). The WHO European review of social determinants of health emphasizes the need for action on social determinants of health across the life course, and, in wider social and economic spheres, to achieve greater health equity as well as to protect future generations. Moreover, it recommends for all countries that the highest priority be given “to ensure a good start to life for every child” (Marmot 2012).
In advanced societies dominated by knowledge-driven economic activities, it has become increasingly important for people to have the knowledge, skills and social contacts necessary for work in this sector. As a consequence of economic restructuring towards knowledge-driven production, cognitive ability and education has moved to the forefront as one of the most influential factors for life-long wellbeing. People lacking education, formal training and skills tend to fall behind, which is reflected in unemployment, social exclusion and poverty. Paradoxically, scientists have argued that while reducing intergenerational transmission of social (dis)advantage, welfare systems increase the scope for social selection into higher social positions on the basis of personal characteristics, such as cognitive ability and personality profiles (Mackenbach 2012).
Statistics on ethnic groups show differences in labour force participation, which reinforces a social duality where some people benefit from work income and welfare systems, whereas others are more or less disconnected and excluded. Systematic variations of this kind also strengthen residential segregation, moving people with varying resources further apart, which in turn creates contrasting living conditions for young generations. This process of cumulative disadvantage is undesirable because it undermines democratic values, brings inefficient use of scarce resources, and creates intolerable health inequalities (CSDH, 2008).

Based on this line of thought, the proposed research programme is influenced by the notion of diorama, in which the life situation of people is best appreciated holistically on the basis of their everyday contexts (Hägerstrand 1982). The overarching research problem neither knows any academic borders, nor is it confined by sector-specific organizations and authorities. Intensified communication between the research community and decision-makers at different levels of society is necessary. Importantly, there is a potential for intervention research and policy making to be enhanced through the systematic use of research based on microdata. Results from interventions and register data can be combined in order to predict long term costs and consequences and in that way generate evidence for successful health and social policies. Of particular interest are analyses of drivers of health care costs and outcomes of preventive measures. The philosophy in medicine is to use the best available evidence. The adoption of the same principle in all societal decision-making will benefit the overall health of the current population and of future generations.

Achievements in previous work: As one of the major results of our efforts within the first round of the SIMSAM initiative, we have moved from words to deeds by acquiring the necessary permissions to combine longitudinal register data covering demographic, socioeconomic and health indicators for the entire Swedish population over several decades. By accessing (starting February 2013) this world-class and unique microdata infrastructure, we have the means to boost our efforts in investigating how different aspects of childhood interplay in determining life courses. To make an optimal use of this new infrastructure we have established a laboratory for interdisciplinary collaboration (the Umeå SIMSAM Lab, inaugurated in January 2013) that works as a nexus for more than 60 scholars representing a wide range of disciplines. The Lab hosts workshops and seminars as well as interdisciplinary research groups taking advantage of our unique data.

REFERENCES
Bråbäck L, Forsberg B. (2009). Environ Health 8:17.
Briggs A, Sculpher M, Claxton K. (2006). Decision Modelling for Health Economic Evaluation. New York, Oxford University Press.
Daly M. (2005). European Societies 7 (3): 379-398.
de Goede J, Putters K, van der Grinten T & van Oers HA. (2010). Health Research Policy and Systems 9(26), 1–11.
de Luna X, Waernbaum I, and Richardson T. (2011). Biometrika 98(4): 861-875.
Goetgeluk S, Vansteelandt S and Goetghebeur E. (2008). Journal of the Royal Statistical Society Series B-Statistical Methodology 70: 1049-1066.
Gustafsson J-E, Allodi M Westling, Alin Åkerman B, Eriksson C, Eriksson L. Fischbein S, Granlund M, Gustafsson P. Ljungdahl S, Ogden T, Persson RS. (2010). School, Learning and Mental Health. A systematic review. Stockholm: Kungl. Vetenskapsakademien.
Hägerstrand T. (1982). Tijdschrift voor economische en sociale geografie 73:6, 329-339.
Hanney SR, Gonzalez-Block MA, Buxton MJ & Kogan M. (2003). Health Research Policy and Systems 1(2).
Holm E, Mäkilä K. (2013). Design Principles for Micro Models. In Spatial Microsimulation: A Reference Guide for Users, Eds: Tanton R, Edwards K, Understanding Population Trends and Processes 6. Springer.
Irwin LG, Siddiqi A & Hertzman C. (2007). Early child development: a powerful equalizer. Final Report for the World Health Organization’s Commission on the Social Determinants of Health.
Josefesson M, de Luna X, Pudas S, Nilsson L-G, Nyberg L. (2012). J of the American Geriatric Association 60(12): 2308-2312.
Kommissionen för ett socialt hållbart Malmö (2013). Malmös väg mot en hållbar framtid. Hälsa, välfärd och rättvisa. Malmö stad.
Leventhal T, & Brooks-Gunn J. (2000). Psychological bulletin 126(2), 309.
Lievens A, Van Aelst S, Van den Bulcke M & Goetghebeur, E. (2013). Plos One 7(11), Article Number: e47112 DOI: 10.1371/journal.pone.0047112
Lowe A, Bråbäck L, Ekeus C, Hjern A, Forsberg B (2011). J Allergy Clin Immunol 128(5):1107-9.
Lundahl L (2012). Leaving school for what? Notes on school-to-work transitions and school dropout in Norway and Sweden. In: T. Strand & M. Roos (eds.). Education for Social Justice, Equity and Diversity. Zürich: LIT Verlag, pp. 85-108.
Mackenbach JP. (2012). Soc Sci Med 75:761-9.
Marmot M, Allen J, Bell R, Bloomer E, Goldblatt P; Consortium for the European Review of Social Determinants of Health and the Health Divide (2012). Lancet 380 (9846): 1011-29. doi: 10.1016/S0140-6736(12)61228-8. Epub 2012 Sep 8. Review.
Mishra GD, Chiesa F, Goodman A, De Stavola B, Koupil I-. (2013). European Journal of Epidemiology 28: 139-147.
Petersen S, Bergström E, Cederblad M, Ivarsson A, Köhler L, Rydell A Stenbeck M, Sundelin C, Hägglöf B. (2010). Barns och ungdomars psykiska hälsa i Sverige: en systematisk litteraturöversikt med tonvikt på förändringar över tid. Stockholm: Kungl. Vetenskapsakademien.
Pollock G. (2007). J Roy Stat Soc A 170: 167–183.
Salonen Tapio. (2012). Barns ekonomiska utsatthet i Sverige årsrapport 2012, Rädda Barnen, Stockholm.
Skolverket (2010). What influences Educational Achievement in Swedish Schools? A Systematic Review and Summary Analysis. Stockholm: Skolverket.
Strandh M, Hammarström A, Nilsson K, Nordenmark M and Russel H. (2013). Sociology of Health and Illness. doi: 10.1111/j.1467-9566.2012.01517.x. [Epub ahead of print]
Vansteelandt S, Goetghebeur E, Kenward MG and Molenberghs G. (2006). Statistica Sinica 16: 953-979.
West P, Sweeting H & Leyland A. (2004). School effects on pupils‟ health behaviours: evidence in support of the health promoting school. Research papers in Education 19(3), 261–292.
WHO (2008). Closing the gap in a generation – health equity through action on the social determinants of health. Final report of the Commission on Social Determinants of Health. Geneva, World Health Organization.