Road traffic noise and risk for cardiovascular disease and diabetes Mette Sørensen, Senior Researcher Danish Cancer Society Research Centre.

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Presentation transcript:

Road traffic noise and risk for cardiovascular disease and diabetes Mette Sørensen, Senior Researcher Danish Cancer Society Research Centre

Road traffic noise and MI No adjustment for air pollution Wolfgang Babisch, Noise and Health, 2008 Meta-analyses of 7 case-control and cohort studies on road traffic noise and myocardial infarction (MI) Dose-response relationship Babisch W, Noise and Health 2008; 10:27-33

Road traffic noise and MI Two studies after 2008 included both road traffic noise and air pollution: 1.Selander, Epidemiology, 2009 Road traffic noise increase risk for incident MI after adjustment for air pollution (modeled NO 2 ) 2.Beelen, Occup Environ Med, 2009 Before air pollution adjustment weak tendency to higher risk for mortality from IHD at road traffic noise > 65 dB After adjustment (BS, traffic intensity) no association Lund, April 2013

Stroke and diabetes Lund, April 2013 STROKE Many risk factors in common with MI Major risk factor is hypertension WHO: 15 million people suffer stroke each year DIABETES Stress and sleep disturbances has been associated with Insulin resistance High morning glucose Appetite regulation Type 2 diabetes WHO: at least 171 million people worldwide have diabetes

Hypotheses Exposure to road traffic noise increase the risk for: Incident myocardial infarction Incident stroke Diabetes -> also after adjusting for air pollution Lund, April 2013

The cohort Diet, Cancer and Health cohort Enrolment in persons aged years invited Copenhagen and Aarhus participated Questionnaire (diet, smoking, alcohol, education etc.) Weight, height and waist circumference measured Lund, April 2013

Noise exposure Addresses Central Population Registry Since 1971 all residents addresses (incl. change of address) recorded All residential addresses between 1987 and 2006 using the PIN Complete address history for participants All in all addresses Geocoded Lund, April 2013

Noise exposure SoundPLAN – the Nordic Prediction Method Geographical coordinates for each address ( addresses) Height (floor) for each address Building polygons All road lines with > 1000 vehicles Traffic composition (heavy/light) Yearly average daily traffic Traffic speed Lund, April 2013

Road noise at enrolment L den, dBNPercent < – – – – – Lund, April 2013

Air pollution Danish AirGIS modeling system Dispersion model At each address from 1987 until 2006 Calculates the sum of: local, urban background and regional background contributions NO x : indicator of air pollution; correlates with traffic such as ultrafine particles (r = 0.93) and PM10 (r = 0.70) Lund, April 2013

Identification of cases Myocardial infarction (MI) and stroke Danish National Hospital Registry (1977): registers ALL discharges from Danish hospitals follow-up cohort using PIN (censoring in 2006) MI: also validation using medical records Primary event - exclude participants with stroke/MI before enrolment In total 1881 stroke cases and 1600 MI cases Lund, April 2013

Identification of cases Diabetes The National Diabetes Registry (1995) Registers all diabetes based on information from other registers: Hospital admission (National Hospital Registry) Medication (National Prescription Registry) Reimbursement for chiropody due to diabetes (National Health Service Registry) Blood glucose tests (National Health Service Registry) In total 3869 cases Exclude participants with diabetes before enrolment (questionnaire) Lund, April 2013

Design Cox proportional hazard model Follow-up until: stroke/MI/diabetes (event), death, emigration or censoring (June 2006) Age underlying time Road traffic noise: time-varying - annual mean of L den at the address at time of diagnosis (5-y preceding diagnosis) Adjustment: sex, calendar-year, socioeconomic factors, railways and airport noise, air pollution (NO x ) Lifestyle confounders, e.g. smoking status, BMI and intake of fruit, vegetables and alcohol Lund, April 2013

Results, stroke/MI L den, per 10 dB Stroke Cases Stroke Adjusted IRR (95% CI) MI Cases MI Adjusted IRR (95% CI) All (1.03–1.25) ( ) Sex Men (1.02–1.27) ( ) Women (1.00–1.28) ( ) Age at event < 65 y (0.91–1.14)* ( ) 65 y (1.13–1.43)* ( ) * P interaction (< 0.001) Lund, April 2013 Adjusted for age, sex, BMI, lifestyle habits, socioeconomic factors, railway and airport noise, air pollution

Results, rcs StrokeMyocardial infarction Lund, April 2013

Results, stroke age Lund, April 2013

Results, diabetes Lund, April 2013 Road traffic noise L den, per 10 dB Diabetes Cases Diabetes Adjusted IRR (95% CI) All diabetes Noise at diagnosis ( ) 5-y noise average preceding diagnosis ( ) Confirmed diabetes * Noise at diagnosis ( ) 5-y noise average preceding diagnosis ( ) * Exclusion of cases only included in the National Diabetes Registry based on blood glucose tests. Adjusted for age, sex, BMI, waist circumference, lifestyle habits, socioeconomic factors, railway and airport noise, air pollution

Results, diabetes Lund, April 2013

Conclusions Exposure to residential road traffic noise was associated with a higher risk for stroke, MI and diabetes For stroke the association was strongest among the oldest For stroke indications of threshold limit around 60 dB For MI no threshold limit For diabetes indications of level off around 65 dB Lund, April 2013

Strenghts Large study with good power Prospective design Follow-up in nationwide registers For MI – validation by medical records Historical address information Adjustment for air pollution Lund, April 2013

Weaknesses No information on noise barriers No information on the bedroom location Stroke – no information on subtype (hemorrhagic/ischemic) Diabetes – unknown whether type I or II (though exclusion of all diabetes before age 50) Lund, April 2013

Co-authors Danish Cancer Society: Ole Raaschou-Nielsen, Zorana Andersen, Rikke Baastrup, Anne Tjønneland Danish EPA: Jørgen Jakobsen Aarhus University, Denmark: Kim Overvad, Martin Hvidberg, Steen Jensen Rambøll, Denmark: Kenneth Lillelund Utrecht University, The Netherlands: Rob Beelen FUNDING: Danish EPA Research Centre for Environmental Health, Danish Ministry of the Interior and Health European Research Council, EU 7th Research Framework Programme (grant ) Lund, April 2013

Thank you for your attention