Road traffic noise and hypertension: results from a cross-sectional public health survey in southern Sweden
1 Department of Occupational and Environmental Medicine, Lund University Hospital, Lund, Sweden
2 Department of Physical Geography and Ecosystems Analysis, Lund University, Lund, Sweden
3 Department of Clincal Sciences, Malmö, Division of Social Medicine and Global Health, Malmö University Hospital, Malmö, Sweden
4 Competence Center for Clinical Research, Lund University Hospital, SE-221 85 Lund, Sweden
Environmental Health 2009, 8:38 doi:10.1186/1476-069X-8-38Published: 10 September 2009
Results from studies of road traffic noise and hypertension are heterogeneous with respect to effect size, effects among males and females and with respect to effects across age groups. Our objective was to further explore these associations.
The study used cross-sectional public health survey data from southern Sweden, including 24,238 adults (18 - 80 years old). We used a geographic information system (GIS) to assess the average road noise (LAeq 24 hr) at the current residential address. Effects on self-reported hypertension were estimated by logistic regression with adjustment for age, sex, BMI, alcohol intake, exercise, education, smoking and socioeconomic status.
Modest exposure effects (OR ≈ 1.1) were generally noted in intermediate exposure categories (45 -64 dB(A)), and with no obvious trend. The effect was more pronounced at > 64 dB(A) (OR 1.45, 95% CI 1.04 - 2.02). Age modified the relative effect (p = 0.018). An effect was seen among middle-aged (40 - 59 years old) at noise levels 60 - 64 dB(A) (OR = 1.27, 95% CI 1.02 - 1.58)) and at > 64 dB(A) (OR = 1.91, 95% CI 1.19 - 3.06)). An effect was also indicated among younger adults but not among elderly. No apparent effect modification by gender, country of origin, disturbed sleep or strained economy was noted.
The study supports an association between road traffic noise at high average levels and self-reported hypertension in middle-aged. Future studies should use age group -specific relative effect models to account for differences in prevalence.