Exposure to road traffic and railway noise and associations with blood pressure and self-reported hypertension: a cohort study

<p>Abstract</p> <p>Background</p> <p>Epidemiological studies suggest that long-term exposure to transport noise increases the risk for cardiovascular disorders. The effect of transport noise on blood pressure and hypertension is uncertain.</p> <p>Methods</p> <p>In 1993-1997, 57,053 participants aged 50-64 year were enrolled in a population-based cohort study. At enrolment, systolic and diastolic blood pressure was measured. Incident hypertension during a mean follow-up of 5.3 years was assessed by questionnaire. Residential long-term road traffic noise (L_den) was estimated for 1- and 5-year periods preceding enrolment and preceding diagnosis of hypertension. Residential exposure to railway noise was estimated at enrolment. We conducted a cross-sectional analysis of associations between road traffic and railway noise and blood pressure at enrolment with linear regression, adjusting for long-term air pollution, meteorology and potential lifestyle confounders (N = 44,083). Incident self-reported hypertension was analyzed with Cox regression, adjusting for long-term air pollution and potential lifestyle confounders.</p> <p>Results</p> <p>We found a 0.26 mm Hg higher systolic blood pressure (95% confidence intervals (CI): -0.11; 0.63) per 10 dB(A) increase in 1-year mean road traffic noise levels, with stronger associations in men (0.59 mm Hg (CI: 0.13; 1.05) per 10 dB(A)) and older participants (0.65 mm Hg (0.08; 1.22) per 10 dB(A)). Road traffic noise was not associated with diastolic blood pressure or hypertension. Exposure to railway noise above 60 dB was associated with 8% higher risk for hypertension (95% CI: -2%; 19%, P = 0.11).</p> <p>Conclusions</p> <p>While exposure to road traffic noise was associated with systolic blood pressure in subgroups, we were not able to identify associations with hypertension.</p

Application of geographic information systems and simulation modelling to dental public health: Where next?

Public health research in dentistry has used geographic information systems since the 1960s. Since then, the methods used in the field have matured, moving beyond simple spatial associations to the use of complex spatial statistics and, on occasions, simulation modelling. Many analyses are often descriptive in nature; however, and the use of more advanced spatial simulation methods within dental public health remains rare, despite the potential they offer the field. This review introduces a new approach to geographical analysis of oral health outcomes in neighbourhoods and small area geographies through two novel simulation methods-spatial microsimulation and agent-based modelling. Spatial microsimulation is a population synthesis technique, used to combine survey data with Census population totals to create representative individual-level population datasets, allowing for the use of individual-level data previously unavailable at small spatial scales. Agent-based models are computer simulations capable of capturing interactions and feedback mechanisms, both of which are key to understanding health outcomes. Due to these dynamic and interactive processes, the method has an advantage over traditional statistical techniques such as regression analysis, which often isolate elements from each other when testing for statistical significance. This article discusses the current state of spatial analysis within the dental public health field, before reviewing each of the methods, their applications, as well as their advantages and limitations. Directions and topics for future research are also discussed, before addressing the potential to combine the two methods in order to further utilize their advantages. Overall, this review highlights the promise these methods offer, not just for making methodological advances, but also for adding to our ability to test and better understand theoretical concepts and pathways