Dataset Information

Highway proximity associated with cardiovascular disease risk: the influence of individual-level confounders and exposure misclassification.

ABSTRACT:

Background

Elevated cardiovascular disease risk has been reported with proximity to highways or busy roadways, but proximity measures can be challenging to interpret given potential confounders and exposure error.

Methods

We conducted a cross sectional analysis of plasma levels of C-Reactive Protein (hsCRP), Interleukin-6 (IL-6), Tumor Necrosis Factor alpha receptor II (TNF-RII) and fibrinogen with distance of residence to a highway in and around Boston, Massachusetts. Distance was assigned using ortho-photo corrected parcel matching, as well as less precise approaches such as simple parcel matching and geocoding addresses to street networks. We used a combined random and convenience sample of 260 adults >40 years old. We screened a large number of individual-level variables including some infrequently collected for assessment of highway proximity, and included a subset in our final regression models. We monitored ultrafine particle (UFP) levels in the study areas to help interpret proximity measures.

Results

Using the orthophoto corrected geocoding, in a fully adjusted model, hsCRP and IL-6 differed by distance category relative to urban background: 43% (-16%,141%) and 49% (6%,110%) increase for 0-50 m; 7% (-39%,45%) and 41% (6%,86%) for 50-150 m; 54% (-2%,142%) and 18% (-11%,57%) for 150-250 m, and 49% (-4%, 131%) and 42% (6%, 89%) for 250-450 m. There was little evidence for association for TNF-RII or fibrinogen. Ortho-photo corrected geocoding resulted in stronger associations than traditional methods which introduced differential misclassification. Restricted analysis found the effect of proximity on biomarkers was mostly downwind from the highway or upwind where there was considerable local street traffic, consistent with patterns of monitored UFP levels.

Conclusion

We found associations between highway proximity and both hsCRP and IL-6, with non-monotonic patterns explained partly by individual-level factors and differences between proximity and UFP concentrations. Our analyses emphasize the importance of controlling for the risk of differential exposure misclassification from geocoding error.

SUBMITTER: Brugge D

PROVIDER: S-EPMC3907023 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Publications

Highway proximity associated with cardiovascular disease risk: the influence of individual-level confounders and exposure misclassification.

Brugge Doug D Lane Kevin K Padró-Martínez Luz T LT Stewart Andrea A Hoesterey Kyle K Weiss David D Wang Ding Ding DD Levy Jonathan I JI Patton Allison P AP Zamore Wig W Mwamburi Mkaya M

Environmental health : a global access science source 20131003 1

<h4>Background</h4>Elevated cardiovascular disease risk has been reported with proximity to highways or busy roadways, but proximity measures can be challenging to interpret given potential confounders and exposure error.<h4>Methods</h4>We conducted a cross sectional analysis of plasma levels of C-Reactive Protein (hsCRP), Interleukin-6 (IL-6), Tumor Necrosis Factor alpha receptor II (TNF-RII) and fibrinogen with distance of residence to a highway in and around Boston, Massachusetts. Distance wa ...[more]

PMID: 24090339

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Project description:BackgroundThe growing interest in research on the health effects of near-highway air pollutants requires an assessment of potential sources of error in exposure assignment techniques that rely on residential proximity to roadways.MethodsWe compared the amount of positional error in the geocoding process for three different data sources (parcels, TIGER and StreetMap USA) to a "gold standard" residential geocoding process that used ortho-photos, large multi-building parcel layouts or large multi-unit building floor plans. The potential effect of positional error for each geocoding method was assessed as part of a proximity to highway epidemiological study in the Boston area, using all participants with complete address information (N = 703). Hourly time-activity data for the most recent workday/weekday and non-workday/weekend were collected to examine time spent in five different micro-environments (inside of home, outside of home, school/work, travel on highway, and other). Analysis included examination of whether time-activity patterns were differentially distributed either by proximity to highway or across demographic groups.ResultsMedian positional error was significantly higher in street network geocoding (StreetMap USA = 23 m; TIGER = 22 m) than parcel geocoding (8 m). When restricted to multi-building parcels and large multi-unit building parcels, all three geocoding methods had substantial positional error (parcels = 24 m; StreetMap USA = 28 m; TIGER = 37 m). Street network geocoding also differentially introduced greater amounts of positional error in the proximity to highway study in the 0-50 m proximity category. Time spent inside home on workdays/weekdays differed significantly by demographic variables (age, employment status, educational attainment, income and race). Time-activity patterns were also significantly different when stratified by proximity to highway, with those participants residing in the 0-50 m proximity category reporting significantly more time in the school/work micro-environment on workdays/weekdays than all other distance groups.ConclusionsThese findings indicate the potential for both differential and non-differential exposure misclassification due to geocoding error and time-activity patterns in studies of highway proximity. We also propose a multi-stage manual correction process to minimize positional error. Additional research is needed in other populations and geographic settings.

Project description:BackgroundDigital proximity tracing (DPT) aims to complement manual contact tracing (MCT) in identifying exposed contacts and preventing further transmission of SARS-CoV-2 in the population. Although several DPT apps, including SwissCovid, have shown to have promising effects on mitigating the pandemic, several challenges have impeded them from fully achieving the desired results. A key question now relates to how the effectiveness of DPT can be improved, which requires a better understanding of factors influencing its processes.ObjectiveIn this study, we aim to provide a detailed examination of the exposure notification (EN) cascade and to evaluate potential contextual influences for successful receipt of an EN and subsequent actions taken by cases and contacts in different exposure settings.MethodsWe used data from 285 pairs of SARS-CoV-2-infected cases and their contacts within an observational cohort study of cases and contacts identified by MCT and enrolled between August 6, 2020, and January 17, 2021, in the canton of Zurich, Switzerland. We surveyed participants with electronic questionnaires. Data were summarized descriptively and stratified by exposure setting.ResultsWe found that only 79 (58.5%) of 135 contacts using the SwissCovid app whose corresponding cases reported to have triggered the EN also received one. Of these, 18 (22.8%) received the EN before MCT. Compared to those receiving an EN after MCT (61/79, 77.2%), we observed that a higher proportion of contacts receiving an EN before MCT were exposed in nonhousehold settings (11/18, 61.1%, vs 34/61, 55.7%) and their corresponding cases had more frequently reported mild-to-moderate symptoms (14/18, 77.8%, vs 42/61, 68.9%). Of the 18 contacts receiving an EN before MCT, 14 (77.8%) took recommended measures: 12 (66.7%) were tested for SARS-CoV-2, and 7 (38.9%) called the SwissCovid Infoline. In nonhousehold settings, the proportion of contacts taking preventive actions after receiving an EN was higher compared to same-household settings (82%, vs 67%). In addition, 1 (9%) of 11 ENs received in the nonhousehold setting before MCT led to the identification of a SARS-CoV-2-infected case by prompting the contact to get tested. This corresponds to 1 in 85 exposures of a contact to a case in a nonhousehold setting, in which both were app users and the case triggered the EN.ConclusionsOur descriptive evaluation of the DPT notification cascade provides further evidence that DPT is an important complementary tool in pandemic mitigation, especially in nonhousehold exposure settings. However, the effect of DPT apps can only be exerted if code generation processes are efficient and exposed contacts are willing to undertake preventive actions. This highlights the need to focus efforts on keeping barriers to efficient code generation as low as possible and promoting not only app adoption but also compliance with the recommended measures upon an EN.Trial registrationInternational Standard Randomised Controlled Trial Number Registry 14990068; https://doi.org/10.1186/ISRCTN14990068.

Dataset Information

Highway proximity associated with cardiovascular disease risk: the influence of individual-level confounders and exposure misclassification.

Background

Methods

Results

Conclusion

Publications

Highway proximity associated with cardiovascular disease risk: the influence of individual-level confounders and exposure misclassification.

Similar Datasets

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