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Longitudinal Analysis of Long-Term Air Pollution Levels and Blood Pressure: A Cautionary Tale from the Multi-Ethnic Study of Atherosclerosis.

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Title: Longitudinal Analysis of Long-Term Air Pollution Levels and Blood Pressure: A Cautionary Tale from the Multi-Ethnic Study of Atherosclerosis.
Authors: Adar, Sara D.1 sadar@umich.edu, Yeh-Hsin Chen2,3, D'Souza, Jennifer C.1, O'Neill, Marie S.1,3, Szpiro, Adam A.4, Auchincloss, Amy H.5, Sung Kyun Park1, Daviglus, Martha L.6,7, Diez Roux, Ana V.5, Kaufman, Joel D.8,9,10
Source: Environmental Health Perspectives. Oct2018, Vol. 126 Issue 10, p1-11. 11p. 2 Charts, 4 Graphs.
Subject Terms: *Air pollution, Hypertension risk factors, Blood pressure, Confidence intervals, Longitudinal method, Research methodology, Regression analysis, Mathematical variables, Proportional hazards models, Data analysis software, Descriptive statistics
Abstract: BACKGROUND: Air pollution exposures are hypothesized to impact blood pressure, yet few longitudinal studies exist, their findings are inconsistent, and different adjustments have been made for potentially distinct confounding by calendar time and age. OBJECTIVE: We aimed to investigate the associations of long- and short-term PM2.5 and NO2 concentrations with systolic and diastolic blood pressures and incident hypertension while also accounting for potential confounding by age and time. METHODS: Between 2000 and 2012, Multi-Ethnic Study of Atherosclerosis participants were measured for systolic and diastolic blood pressure at five exams. We estimated annual average and daily PM2.5 and NO2 concentrations for 6,569 participants using spatiotemporal models and measurements, respectively. Associations of exposures with blood pressure corrected for medication were studied using mixed-effects models. Incident hypertension was examined with Cox regression. We adjusted all models for sex, race/ethnicity, socioeconomic status, smoking, physical activity, diet, season, and site. We compared associations from models adjusting for time-varying age with those that adjusted for both time-varying age and calendar time. RESULTS: We observed decreases in pollution and blood pressures (adjusted for age and medication) over time. Strong, positive associations of longand short-term exposures with blood pressure were found only in models with adjustment for time-varying age but not adjustment for both time-varying age and calendar time. For example, 16-ppb higher annual average NO2 concentrations were associated with 2.7 (95% CI: 1.5, 4.0) and -0.8 (95% CI: -2.6, 1.0) mmHg in systolic blood pressure with and without additional adjustment for time, respectively. Associations with incident hypertension were similarly weakened by additional adjustment for time. Sensitivity analyses indicated that air pollution did not likely cause the temporal trends in blood pressure. CONCLUSIONS: In contrast to experimental evidence, we found no associations between long- or short-term exposures to air pollution and blood pressure after accounting for both time-varying age and calendar time. This research suggests that careful consideration of both age and time is needed in longitudinal studies with trending exposures. [ABSTRACT FROM AUTHOR]
Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Longitudinal Analysis of Long-Term Air Pollution Levels and Blood Pressure: A Cautionary Tale from the Multi-Ethnic Study of Atherosclerosis.
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  Data: <searchLink fieldCode="AR" term="%22Adar%2C+Sara+D%2E%22">Adar, Sara D.</searchLink><relatesTo>1</relatesTo><i> sadar@umich.edu</i><br /><searchLink fieldCode="AR" term="%22Yeh-Hsin+Chen%22">Yeh-Hsin Chen</searchLink><relatesTo>2,3</relatesTo><br /><searchLink fieldCode="AR" term="%22D'Souza%2C+Jennifer+C%2E%22">D'Souza, Jennifer C.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22O'Neill%2C+Marie+S%2E%22">O'Neill, Marie S.</searchLink><relatesTo>1,3</relatesTo><br /><searchLink fieldCode="AR" term="%22Szpiro%2C+Adam+A%2E%22">Szpiro, Adam A.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Auchincloss%2C+Amy+H%2E%22">Auchincloss, Amy H.</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Sung+Kyun+Park%22">Sung Kyun Park</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Daviglus%2C+Martha+L%2E%22">Daviglus, Martha L.</searchLink><relatesTo>6,7</relatesTo><br /><searchLink fieldCode="AR" term="%22Diez+Roux%2C+Ana+V%2E%22">Diez Roux, Ana V.</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Kaufman%2C+Joel+D%2E%22">Kaufman, Joel D.</searchLink><relatesTo>8,9,10</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Health+Perspectives%22">Environmental Health Perspectives</searchLink>. Oct2018, Vol. 126 Issue 10, p1-11. 11p. 2 Charts, 4 Graphs.
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  Data: *<searchLink fieldCode="DE" term="%22Air+pollution%22">Air pollution</searchLink><br /><searchLink fieldCode="DE" term="%22Hypertension+risk+factors%22">Hypertension risk factors</searchLink><br /><searchLink fieldCode="DE" term="%22Blood+pressure%22">Blood pressure</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink><br /><searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+variables%22">Mathematical variables</searchLink><br /><searchLink fieldCode="DE" term="%22Proportional+hazards+models%22">Proportional hazards models</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: BACKGROUND: Air pollution exposures are hypothesized to impact blood pressure, yet few longitudinal studies exist, their findings are inconsistent, and different adjustments have been made for potentially distinct confounding by calendar time and age. OBJECTIVE: We aimed to investigate the associations of long- and short-term PM2.5 and NO2 concentrations with systolic and diastolic blood pressures and incident hypertension while also accounting for potential confounding by age and time. METHODS: Between 2000 and 2012, Multi-Ethnic Study of Atherosclerosis participants were measured for systolic and diastolic blood pressure at five exams. We estimated annual average and daily PM2.5 and NO2 concentrations for 6,569 participants using spatiotemporal models and measurements, respectively. Associations of exposures with blood pressure corrected for medication were studied using mixed-effects models. Incident hypertension was examined with Cox regression. We adjusted all models for sex, race/ethnicity, socioeconomic status, smoking, physical activity, diet, season, and site. We compared associations from models adjusting for time-varying age with those that adjusted for both time-varying age and calendar time. RESULTS: We observed decreases in pollution and blood pressures (adjusted for age and medication) over time. Strong, positive associations of longand short-term exposures with blood pressure were found only in models with adjustment for time-varying age but not adjustment for both time-varying age and calendar time. For example, 16-ppb higher annual average NO2 concentrations were associated with 2.7 (95% CI: 1.5, 4.0) and -0.8 (95% CI: -2.6, 1.0) mmHg in systolic blood pressure with and without additional adjustment for time, respectively. Associations with incident hypertension were similarly weakened by additional adjustment for time. Sensitivity analyses indicated that air pollution did not likely cause the temporal trends in blood pressure. CONCLUSIONS: In contrast to experimental evidence, we found no associations between long- or short-term exposures to air pollution and blood pressure after accounting for both time-varying age and calendar time. This research suggests that careful consideration of both age and time is needed in longitudinal studies with trending exposures. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1289/EHP2966
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 1
    Subjects:
      – SubjectFull: Air pollution
        Type: general
      – SubjectFull: Hypertension risk factors
        Type: general
      – SubjectFull: Blood pressure
        Type: general
      – SubjectFull: Confidence intervals
        Type: general
      – SubjectFull: Longitudinal method
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      – SubjectFull: Research methodology
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      – SubjectFull: Regression analysis
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      – SubjectFull: Mathematical variables
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      – SubjectFull: Proportional hazards models
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      – SubjectFull: Data analysis software
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      – SubjectFull: Descriptive statistics
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      – TitleFull: Longitudinal Analysis of Long-Term Air Pollution Levels and Blood Pressure: A Cautionary Tale from the Multi-Ethnic Study of Atherosclerosis.
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              Text: Oct2018
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