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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.
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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 Exposure Health outcome . . . . . . . . Confounding factors Short-term Acute Long term Chronic
Background Air pollution health effects pyramid adapted from WHO
Background Difficulties in air pollution epidemiology: 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
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 Type of investigation: epidemiological cross-sectional study Sampling method: purposive sampling based on exposure status (type of apartment’s heating system) 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
82% of coal heated apartments was located in the districts I and XIII Study Participants District Apartments Subjects I 97 196 II 22 45 III 11 22 IV 14 32 V 9 21 VI 9 20 VII 4 10 VIII 11 28 IX 4 7 X 4 13 XI 30 70 XII 12 26 XIII 50 96 XIV 3 7 XV 8 20 XVI 10 19 XVII 1 4 XVIII 9 21 Total 308 657
Males Females <35 35-65 >65 Characteristics of the study population
Central heating Coal stoves Gas stove Electric appliance Municipal supply Home environment (1)
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: 2.1-4.8, p<0.001 adjusted for age, gender, education, smoking
General health status (2) 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/m3(SD 30.6)
Indoor – respiratory symptoms Multivariate logistic regression models on respiratory symptoms and some indoor sources of air pollution adjusted to age, gender, education, smoking habit
Indoor – spirometry (1) Multivariate regression models on spirometrymeasurements and some indoor sources of air pollution 1/ Dummy variable: 0 vs. <60min, 0 vs. >60 min Adjusted for age, gender, education, BMI, height, occupational exposure
Indoor – spirometry (2) Multivariate linear regression models on spirometrymeasurements and some indoor sources of air pollution 1/ Dummy variable: 0 vs. <60min, 0 vs. >60 min Adjusted for age, gender, education, BMI, height, family history of asthma, occupational exposure
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 Means of Peak Expiratory Flow as percent of predicted values 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
Population Attributable Proportion Risk attributed to PM10 greater than 50g/m3 in population of Kraków Risk attributed to using coal-burning stoves in population of Kraków
Health Impact Assessment Winter 2004/2005: 1.12.2004-31.03.2005: 122 days PM10 distribution: 119 days PM10 > 20 µg/m3 79 days PM10 > 50 µg/m3
Health Impact Assessment Winter 2004/2005: 1.12.2004-31.03.2005: 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 ?
Health Impact Assessment Distribution of daily PM10 levels and associated respiratory admissions (%) How many cases is attributed to air pollution ?
7% 4.3% HIA findings Short-term effects of PM10 on respiratory admissions Number of attributable cases for different scenarios of PM10 reduction
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 mygomola@cyf-kr.edu.pl