Association Between Mould/Dampness in the Home and Health Status of the Inhabitants P. Rudnai 1, M.J.Varró 1, T. Málnási 1, A. Páldy 1, S. Nicol 2, A. O’Dell 2, M. Braubach 3, X. Bonnefoy 3 1 National Institute of Environmental Health, Hungary 2 Building Research Establishment, United Kingdom 3 WHO ECEH Bonn Office

Sources of Dampness in Dwellings A warm, dry well-ventilated home is the ideal. But many are damp: Rising Damp  Capillary action of ground water into the structure Penetrating Damp  Of rain/melt water through the roof, walls, or joints Condensation  Usually generated internally by household through cooking, clothes drying, bathing and breathing.

Rising Damp

Penetrating Damp

Serious Condensation

THE „LARES” STUDY ( ) Angers880 Bonn946 Bratislava892 Budapest 1086 Ferreira 1055 Forli 1157 Geneva710 Vilnius 1793 Altogether 8519 persons interviewed

Dampness/Mould Related Data from WHO LARES Study Mould growth: surveyor’s assessment  extent (room by room): seriousness Smell, condensation: surveyor’s assessment  extent (room by room): whether present Mould growth: householder’s views  rooms: frequency: duration Dampness / condensation: householder’s views  Rooms: frequency: duration Information combined to produce index of likelihood and severity:  No mould/dampness  Little mould/dampness  Some mould/dampness  Much mould /dampness

Distribution of homes by mould categories in the LARES Study

‘Much mould / dampness’ by LARES cities

Explanation for dampness Wide variation in dampness between 8 LARES cities Main factors: Disrepair, lack of central heating, home perceived as cold in winter. These factors are good predictors of dampness in each city Model predicts Geneva as best, Ferreira as worst, and most in-between. ‘City’ is still a factor.

The Relationship Between Illness and Dampness Relationship explored by plotting persons affected by the different illnesses against the damp/mould index Criterion for an association:  Doctor diagnosed diseases and symptoms  Significant association, using tabulation and logistic regression (bi and multi-variant) using STATA 7.0 program.  Evidence of a dose effect

Prevalences of some chronic diseases by mould/dampness categories *p<0.05 **p<0.01 ***p<0.001

Prevalences of some chronic diseases by mould/dampness categories *p<0.05 **p<0.01 ***p<0.001

Prevalences of people with some acute illnesses in the last 12 months *p<0.05 **p<0.01 ***p<0.001

Prevalences of some symptoms during the last 12 months by mould/dampness categories *p<0.05 **p<0.01 ***p<0.001

Adjusted odds ratios* of some chronic and acute diseases among people living in homes with much mould/dampness (vs. no mould/dampness) *Adjusted to age, sex, SES, city, smoking and ETS

Adjusted odds ratios* of the prevalence of some symptoms in the last 12 months among people living in homes with much mould/dampness (vs. no mould/dampness) *Adjusted to age, sex, SES, city, smoking and ETS

Results: Apparent associations Significant associations:  Asthma/asthma attack  Chronic bronchitis  Arthrosis and arthritis  Anxiety and depression  Depression (Salsa)  Migraine  Diarrhoeal disease  Cold/throat illness  Wheezing/whistling in the chest  Eczema  Watery eyes/eye inflammation  Headache

Explanations ? Apparent associations with emotional / mental conditions and cold- like symptoms Relationship does not imply anything about cause and effect Relationships:  dampness … illness  dampness … ‘poor housing’ … illness  dampness … ‘poor housing’ … human factors … illness Poor housing is typically lived in by old persons, households with limited means, less education/access to employment. Dissatisfaction (or actual illness) experienced by vulnerable persons within these households may have given rise to these effects. LARES analysis shows that vulnerable people are more likely to suffer from anxiety/depression, but the analysis still indicates a residual ‘dampness/mould’ effect

Conclusions LARES contains reasonable measures of dampness  consistency between household / surveyor views and mould / dampness Dampness is a significant problem, although considerable city- to-city variations  partially explainable  some ‘city’ component remaining Dampness / illness findings consistent with other studies, although difficult to quantify due to small sample sizes ‘Definite’ relationships: emotional / mental conditions and ‘cold-like’ symptoms - others not ruled out  ‘poor housing’ and human factors may mediate  LARES supports the view that people with poor health and negative well being are more likely to live in poor housing.

Thank you for your attention

Recommendations for Governments/Agencies Governments have a responsibility to remove/reduce risk of dampness: Sample house condition surveys – to measure and monitor the effect of dampness (and housing conditions generally) Guidance for home owners/landlords on identifying and rectifying damp/mould. Consider grants to improve homes of those who cannot afford work Building regulations should prevent dampness and the proliferation of indoor allergens in new homes Education for households on the risks of living in damp/mouldy homes and reducing humidity/condensation. Money spent on prevention will save lives/money