From toxic emissions to health effects… Health effects of air pollution in Krakow population Results of epidemiological Krakow study Krystyna Szafraniec, Agnieszka Kiełtyka, Marta Rzepecka Nikolaos Stilianakis, Yoannis Drossinos Anette Borowiak, Luisa Marelli, Herdis Laupsa, Robert Piątek Joanna Niedziałek, Jose Jimenez

Background Human responses to air pollutants ExposureHealth outcome Confounding factors Short-term Acute Long term Chronic

Background Air pollution health effects pyramid adapted from WHO

Background 1. While exposure is common, the risk tend to be low 2. Misclassifaction of exposure - personal exposure to air pollution differ substantially from ambient data 3. Exposure is multifactorial 4. Adverse health effects of environmental pollutants are generally nonspecific Difficulties in air pollution epidemiology:

Background How big is particular health problem? Measures of risk: RR (relative risk), β-coefficient Attributable Proportion

Aim To investigate the health effect caused by particulate matter air pollution in adult population with special attention given to the indoor exposure related to type of apartment’s heating

Study Design epidemiological cross-sectional study Type of investigation:epidemiological cross-sectional study Sampling method:purposive sampling based on exposure status (type of apartment’s heating system) structured questionnaires on Research tools:structured questionnaires on - personal characteristics - health status - daily activity - housing conditions lung functions measure by spirometry tests

Study Design Health outcomes: general health status measured by no. of chronic conditions and SF-36 questionnaire symptoms and diseases of respiratory system (chronic cough, chronic bronchitis, asthma, allergy) functional status of the lung (FVC, FEV1, PEF,…) Indicators of exposure: Indoor air pollution: measurements of indoor air quality (20 apartments) type of apartment’s heating system (coal stoves vs. central heating) gas appliances indoor environment (ETS,dampness, pets) Outdoor air pollution: on site measurements of outdoor PM10 for 20 apartments modelled ambient air quality (PM10) in other apartment’s locations

Study Participants I I II II III III IV IV V 9 21 V 9 21 VI 9 20 VI 9 20 VII 4 10 VII 4 10 VIII VIII IX 4 7 IX 4 7 X 4 13 X 4 13 XI XI XII XII XIII XIII XIV 3 7 XIV 3 7 XV 8 20 XV 8 20 XVI XVI XVII 1 4 XVII 1 4 XVIII 9 21 Total % of coal heated apartments was located in the districts I and XIII District Apartments Subjects

Characteristics of the study population Males Females < >65

Home environment (1) Central heating Coal stoves Gas stove Electric appliance Municipal supply

Home environment (2) Environmental Tobacco Smoke Regular smoking in 174 (56.5%) apartments 147 (37%) non-smoking persons is exposed to ETS in their own apartments ! !

Respiratory symptoms Reported prevalence (%) of respiratory symptoms Which of the symptoms are caused by PM pollution?

General health status (1) Subjective evaluation of health status OR=3.2, 95%CI: , p < adjusted for age, gender, education, smoking

General health status (2) Chronic conditions OR95%CI 1Chronic respiratory diseases – 2.5 2Hypertension Serious disease such as cancer Peptic or duodenal ulcer or serious intestinal disorders for at least 3 mo Liver diseases, bile stones or cholecystitis (excluding tumors) Diabetes Thyroid diseases Diseases of nervous system Persisting back pain for at least 3 months or hernia (excluding possible spine ostheoporosis) Rheumatism or other arthralgia (including arthritis or other serious bone diseases) Migraine or other chronic pain in a head Atopic dermatitis or eczema adjusted to age, gender, education, smoking

Exposure Assessment Indoor air pollution type of heating (coal vs. non-coal) time span of burning coal (in minutes) time span of cooking on a gas stove (in minutes) ETS estimated indoor concentration based on statistical model derived from indoor-outdoor measurements campaign Outdoor air pollution outdoor concentration based on modelled PM10 data for apartment locations on ‘average winter day’ winter PM10 average: 42.7 µg/m 3 (SD 30.6)

Chronic coughChronic bronchitis RR95%CIpRR95%CIp Type of heating 0-central 1-coal 1.88( ) ( )0.036 Stove doors kept open No exposure 1.0 <60 min1.22( ) ( )0.235 >60 min2.12( ) ( )0.031 Using gas oven 0-no, 1-yes 1.30( ) ( )0.017 Multivariate logistic regression models on respiratory symptoms and some indoor sources of air pollution adjusted to age, gender, education, smoking habit Indoor – respiratory symptoms

Multivariate regression models on spirometry measurements and some indoor sources of air pollution 1/ Dummy variable: 0 vs. 60 min Adjusted for age, gender, education, BMI, height, occupational exposure Indoor – spirometry (1) FVCFVC <70%expected  95%CIpRR95%CIp Heating 0-central 1-coal ; ; Stove doors kept open 1 <60 min ; ; >60 min ; ; Cooking on gas oven (10 min.interval) ; ;

Multivariate linear regression models on spirometry measurements and some indoor sources of air pollution 1/ Dummy variable: 0 vs. 60 min Adjusted for age, gender, education, BMI, height, family history of asthma, occupational exposure Indoor – spirometry (2) PEFPEF%  95%CIpRR95%CIp Heating 0-central 1-coal ; ; Stove doors kept open 1 <60 min ; ; >60 min ; ; Stove doors kept open (continuous with 10 min unit of time) ; ;

Outdoor modelled PM10 exposure & respiratory symptoms Proportion of chronic cough, phlegm and bronchitis according to modelled PM10 exposure levels adjusted to type of heating system, age, gender, smoking status, occupational exposure and educational level

Outdoor modelled PM10 exposure & spirometry Means of Peak Expiratory Flow as percent of predicted values according to modelled PM10 exposure levels PEF% adjusted to type of heating system, age, gender, smoking status, occupational exposure, educational level and family history of asthma

Outdoor modelled PM10 exposure & indoor heating Proportion of respiratory symptoms according to type of heating system adjusted to PM10 level, age, gender, smoking status, occupational exposure and educational level adjusted to PM10 level, age, gender, smoking status, occupational exposure, educational level and family history of asthma Means of Peak Expiratory Flow as percent of predicted values according to type of heating system

Population Attributable Proportion Risk attributed to PM10 greater than 50  g/m 3 in population of Kraków Risk attributed to using coal-burning stoves in population of Kraków

Health Impact Assessment 122 days Winter 2004/2005: : 122 days PM10 distribution: 119 daysPM10 > 20 µg/m 3 79 daysPM10 > 50 µg/m 3

Health Impact Assessment 122 days Winter 2004/2005: : 122 days Hospital admissions from respiratory conditions (ICD10: J00-J99) Age: 15 and above 2614 cases ≈ 22 cases daily How many cases is attributed to air pollution ?

Distribution of daily PM10 levels and associated respiratory admissions (%) Health Impact Assessment How many cases is attributed to air pollution ?

Short-term effects of PM10 on respiratory admissions Number of attributable cases for different scenarios of PM10 reduction HIA findings all days Scenario: all daysNAC95%CI above 20 µg/m 3 to 20 µg/m above 50 µg/m 3 to 50 µg/m % 4.3%

The Study was partially done in the Chair of Epidemiology and Preventive Medicine of the Jagiellonian University Medical College and is continued in Epidemiology and Population Studies Department Institute of Public Health of the same University contact: dr Krystyna Szafraniec