Abstract
Purposes
The aim was to develop a new model to identify residential buildings with higher frequencies of “SBS” than expected, “risk buildings”.
Methods
In 2005, 481 multi-family buildings with 10,506 dwellings in Stockholm were studied by a new stratified random sampling. A standardised self-administered questionnaire was used to assess “SBS”, atopy and personal factors. The response rate was 73%. Statistical analysis was performed by multiple logistic regressions.
Results
Dwellers owning their building reported less “SBS” than those renting. There was a strong relationship between socio-economic factors and ownership. The regression model, ended up with high explanatory values for age, gender, atopy and ownership. Applying our model, 9% of all residential buildings in Stockholm were classified as “risk buildings” with the highest proportion in houses built 1961–1975 (26%) and lowest in houses built 1985–1990 (4%).
Conclusion
To identify “risk buildings”, it is necessary to adjust for ownership and population characteristics.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Agnell W, Grimsrud DT (2004) Survey and critical review of scientific literature on indoor air quality, ventilation, and building-related health effects in residences. In. University of Minnesota, Las Vegas
Agresti A, Coull BA (1998) Approximate is better than “Exact” for interval estimation of binomial proportions. Am Stat 52(2):119–126
Andersson K, Ydreborg B, Fagerlund I, Aslaksen W (2005) Socio-economic factors, lifestyle and personal attitudes influence reports of SBS-symptoms in questionnaire surveys. In: Indoor air 2005, Beijing, pp 3736–3740
Anonymous (ed) (2006) Statistical year-book of Stockholm 2007. Stockholm Office of Research and Statistics, Stockholm
Anonymous (ed) (2009) Environmental health report 2009. The Swedish National Board of Health and Welfare. ISBN 978-91-978065-7-2 (in Swedish)
Apter A, Bracker A, Hodgson M, Sidman J, Leung WY (1994) Epidemiology of the sick building syndrome. J Allergy Clin Immunol 94:277–288
Bergh C, Åberg M, Torgrip R, Emenius G, Östman C (2008) Comprehensive analysis of indoor air—untargeted GC/MS analysis of SPE trapped organic compounds for classification of “sick” buildings using uni and multivariate data analysis. In: Indoor air 2008, 17–22 August 2008, Copenhagen, Denmark, paper ID:1087
Björnsson E, Janson C, Norbäck D, Boman G (1998) Symptoms related to the sick building syndrome in general population sample: associations with atopy, bronchial hyper-responsiveness and anxiety. Int J Tuberc Lung Dis 2:1023–1028
Bornehag CG, Blomqvist G, Gyntelberg F, Järvholm B, Malmberg P, Nordvall L, Nielsen A, Pershagen G, Sundell J (2001) Dampness in buildings and health. Nordic interdisciplinary review of the scientific evidence on associations between exposure to “dampness” in buildings and health effects (NORDDAMP). Indoor Air 11:72–86
Emenius G, Hult M, Östman C, Svartengren M, Corner R, Engvall K (2008) Healthy sustainable houses in Stockholm (3H), field study. In: Indoor air 2008, 17–22 August 2008, Copenhagen, Denmark, paper ID:152
Engvall K, Norrby C, Bandel J, Hult M, Norbäck D (2000) Development of a multiple regression model to identify multi-family residential buildings with a high prevalence of sick building syndrome (SBS). Indoor Air 10:101–110
Engvall K, Sandstedt E, Norrby C (2003) The Stockholm Indoor Environment Questionnaire: a sociologically based tool for the assessment of indoor environment and health in dwellings. Indoor Air 13:1–10
Engvall K, Corner R, Emenius G, Hult M (2009) Perceived indoor environment and health in residential buildings in Stockholm 2005. (In Swedish: Upplevd inomhusmiljö och hälsa i Stockholms flerbostadshus 2005.) Available at http://www.ammuppsala.se/3H
Eriksson NM, Stenberg BG (2006) Baseline prevalence of symptoms related to indoor environment. Scand J Public Health 34(4):387–396
Fisk WJ, Lei-Gomez Q, Mendell MJ (2007) Meta-analyses of the associations of respiratory health effects with dampness and mould in homes. Indoor Air 17(4):284–296
Hedge A, Burge PS, Robertson AS, Wilson S, Harris-Bass J (1989) Work-related illness in offices: a proposed model of the “sick building syndrome. Environ Int 15:143–158
Hodgson M (1995) The Sick Building syndrome. Occup Med 10:167–175 (State of the Art Reviews)
Hult M, Corner R, Engvall K, Nordström F, Emenius G (2008) Application of DPSEEA—framework in Stockholm Healthy Sustainable House Study (3H). In: Indoor air 2008, 17–22 August 2008, Copenhagen, Denmark, paper ID:636
Kreiss K (1989) The epidemiology of building-related complaints and illness. Occup Med 4:575–592
Lindström M, Moghaddassi M, Merlo J (2004) Individual self-reported health, social participation and neighbourhood: a multilevel analysis in Malmö, Sweden. Prev Med 39:135–141
Lumley T (2004) Analysis of complex survey samples. J Stat Softw 9(1):1–9
Lumley T (2008) Survey: analysis of complex survey samples. R package version 3.6–5
Mendell MJ (1993) Non-specific symptoms in office workers: a review and summery of epidemiologic literature. Indoor Air 3:227–236
Mizoue T, Andersson K, Reijula K, Fedeli C (2004) Seasonal variation in perceived indoor environment and non-specific symptoms in a temperate climate. J Occup Health 46(4):303–309
Nikić D, Stojanović D (2004) Sick building syndrome—a result of modern lifestyle. Srp Arh Celok Lek 132(7–8):240–245
Norbäck D, Edling C (1991) Environmental, occupational and personal factors related to the prevalence of sick building syndrome in general population. Br J Ind Med 48:451–462
Norbäck D, Edling C, Wieslander G (1993) Sick building syndrome in the general Swedish population—the significance of outdoor and indoor air quality and seasonal variation. In: Indoor air 1993, Helsinki, Finland, 1:273–278
Norlen U, Andersson K (1993) An indoor climate survey of the Swedish housing stock (the ELIB study). In: Indoor air 1993, pp 743–748
Rockberger C, Zetterman L (2005) The results from sale of public owned properties during 1999–2004. (In Swedish: Resultatet av de kommunala bostadsbolagens fastighetsförsäljningar åren 1999–2005) USK, aktuellt 2005:2, Stockholm Office of Research and Statistics
Seppanen OA, Fisk WJ (2004) Summary of human responses to ventilation. Indoor Air 14(Suppl 7):102–118
Skov P, Valbjorn O, Danish Indoor Study Group (1989) Influence of personal characteristics, job-related factors and psychosocial factors on the sick building syndrome”. Scand J Work Environ Health 15:286–295
R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3_900051-07-0, URL:http://www.R-project.org
Tello J, Eduardo, Jones J, Bonizzato P, Mazzi M, Amaddeo F, Tansella M (2005) A census-based socio-economic status (SES) index as a tool to examine the relationship between mental health service use and deprivation. Soc Sci Med 61:2096–2105
Wang BL, Takigawa T, Yamasaki Y, Sakano N, Wang DH, Ogino K (2008) Symptom definitions for SBS (sick building syndrome) in residential dwellings. Int J Hyg Environ Health 211(1–2):114–120
WHO (1983) Indoor air pollutants: exposure and health effects. EURO Reports and Studies 78, World Health Organization, Copenhagen
Acknowledgments
This study was supported by grants from The City of Stockholm, The Swedish Research Council Formas and Stockholm County Council.
Conflicts of interest statement
The authors declare that they have no conflict of interest.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Engvall, K., Hult, M., Corner, R. et al. A new multiple regression model to identify multi-family houses with a high prevalence of sick building symptoms “SBS”, within the healthy sustainable house study in Stockholm (3H). Int Arch Occup Environ Health 83, 85–94 (2010). https://doi.org/10.1007/s00420-009-0447-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00420-009-0447-0