Studies from different geographical regions have assessed the relations between indoor dampness and mold problems and the risk of asthma, but the evidence has been inconclusive. To assess the relations between indicators of indoor dampness and mold problems and the risk of developing new asthma, and to investigate whether such relations differ according to the type of exposure. A systematic literature search of PubMed database from 1990 through March 2012 and the reference lists of recent reviews and of relevant articles identified in our search. Cohort/longitudinal and incident case-control studies assessing the relation between mold/dampness and new asthma were included. Three authors independently evaluated eligible articles and extracted relevant information using a structured form. Sixteen studies were included: 11 cohort and 5 incident case-control studies. The summary effect estimates (EE) based on the highest and lowest estimates for the relation between any exposure and onset of asthma were 1.50 (95% confidence interval [CI] 1.25–1.80, random-effects model, Q-statistic 38.74 (16), P = 0.001) and 1.31 (95% CI 1.09–1.58, random-effects model, Q-statistic 40.08 (16), P = 0.000), respectively. The summary effect estimates were significantly elevated for dampness (fixed-effects model: EE 1.33, 95% CI 1.12–1.56, Q-statistic 8.22 (9), P = 0.413), visible mold (random-effects model; EE 1.29, 95% CI 1.04–1.60, 30.30 (12), P = 0.001), and mold odor (random-effects model; EE 1.73, 95% CI 1.19–2.50, Q-statistics 14.85 (8), P = 0.038), but not for water damage (fixed-effects model; EE 1.12, 95% CI 0.98–1.27). Heterogeneity was observed in the study-specific effect estimates. The evidence indicates that dampness and molds in the home are determinants of developing asthma. The association of the presence of visible mold and especially mold odor to the risk of asthma points towards mold-related causal agents.

Family history of asthma and other allergic diseases have been linked to the risk of childhood asthma previously, but little is known about their effect on the age-of-onset and persistency of asthma until young adulthood. We assessed the effect of the family history of asthma and allergic diseases on persistent vs. transient, and early- vs. late-onset persistent asthma in The Espoo Cohort Study 1991–2011, a population-based cohort study of 1623 subjects (follow-up rate 63.2%). The determinants were any family history (any parent or sibling); maternal; paternal; siblings only; parents only; and both siblings and parents. Analyses were conducted separately for asthma and allergic diseases while taking the other disease into account as a confounding factor. The outcomes were persistent, transient, early-onset persistent (<13 years) and late-onset persistent asthma. Adjusted risk ratios (RR) were calculated applying Poisson regression. Q-statistics were used to assess heterogeneity between RRs. Family history was associated with the different subtypes but the magnitude of effect varied quantitatively. Any family history of asthma was a stronger determinant of persistent (adjusted RR = 2.82, 95% CI 1.99-4.00) than transient asthma (1.65, 1.03-2.65) (heterogeneity: P = 0.07) and on early-onset than late-onset persistent asthma. Also any family history of allergic diseases was a stronger determinant of persistent and early-onset asthma. The impact of paternal asthma continued to young adulthood (early-onset: 3.33, 1.57-7.06 vs. late-onset 2.04, 0.75-5.52) while the influence of maternal asthma decreased with age (Early-onset 3.94, 2.11-7.36 vs. Late-onset 0.88, 0.28-2.81). Paternal allergic diseases did not follow the pattern of paternal asthma, since they showed no association with late-onset asthma. Also the effect estimates for other subtypes were lower than in other hereditary groups (persistent 1.29, 0.75-2.22 vs. transient 1.20, 0.67-2.15 and early-onset 1.86, 0.95-3.64 vs. late-onset 0.64, 0.22-1.80). Family history of asthma and allergic diseases are strong determinants of asthma, but the magnitude of effect varies according to the hereditary group so that some subtypes have a stronger hereditary component, and others may be more strongly related to environmental exposures. Our results provide useful information for assessing the prognosis of asthma based on a thorough family history.

Background: Despite the recent developments in physically and chemically based analysis of atmospheric particles, no models exist for resolving the spatial variability of pollen concentration at urban scale. Objectives: We developed a land use regression (LUR) approach for predicting spatial fine-scale allergenic pollen concentrations in the Helsinki metropolitan area, Finland, and evaluated the performance of the models against available empirical data. Methods: We used grass pollen data monitored at 16 sites in an urban area during the peak pollen season and geospatial environmental data. The main statistical method was generalized linear model (GLM). Results: GLM-based LURs explained 79% of the spatial variation in the grass pollen data based on all samples, and 47% of the variation when samples from two sites with very high concentrations were excluded. In model evaluation, prediction errors ranged from 6% to 26% of the observed range of grass pollen concentrations. Our findings support the use of geospatial data–based statistical models to predict the spatial variation of allergenic grass pollen concentrations at intra-urban scales. A remote sensing–based vegetation index was the strongest predictor of pollen concentrations for exposure assessments at local scales. Conclusions: The LUR approach provides new opportunities to estimate the relations between environmental determinants and allergenic pollen concentration in human-modified environments at fine spatial scales. This approach could potentially be applied to estimate retrospectively pollen concentrations to be used for long-term exposure assessments. Citation: Hjort J, Hugg TT, Antikainen H, Rusanen J, Sofiev M, Kukkonen J, Jaakkola MS, Jaakkola JJ. 2016. Fine-scale exposure to allergenic pollen in the urban environment: evaluation of land use regression approach. Environ Health Perspect 124:619–626; http://dx.doi.org/10.1289/ehp.1509761