Grantee Research Project Results
2015 Progress Report: Hypertension in Mexican-Americans: Assessing Disparities in Air Pollutant Risks
EPA Grant Number: R834581Title: Hypertension in Mexican-Americans: Assessing Disparities in Air Pollutant Risks
Investigators: Symanski, Elaine , Chan, Wenyaw , Piller, Linda B. , Chen, Lin-An , Lopez, David S , Strom, Sara , Jimenez, Maria
Current Investigators: Symanski, Elaine , Bondy, Melissa L. , Chen, Lin-An , Jimenez, Maria , Strom, Sara , Chan, Wenyaw
Institution: National Chiao-Tung University , The University of Texas Health Science Center at San Antonio , The University of Texas MD Anderson Cancer Center , The University of Texas School of Public Health
Current Institution: The University of Texas School of Public Health , National Chiao-Tung University , The University of Texas MD Anderson Cancer Center
EPA Project Officer: Hahn, Intaek
Project Period: August 1, 2010 through July 31, 2014 (Extended to July 31, 2016)
Project Period Covered by this Report: August 1, 2014 through July 31,2015
Project Amount: $1,250,000
RFA: Understanding the Role of Nonchemical Stressors and Developing Analytic Methods for Cumulative Risk Assessments (2009) RFA Text | Recipients Lists
Research Category: Human Health
Objective:
We are assessing the hypothesis that individual- and neighborhood-level psychosocial stressors exacerbate risks for hypertension associated with fine particulates and other air pollutants among individuals of Mexican origin living in Houston, Texas, who are also participating in the University of Texas MD Anderson Cancer Center’s Mano a Mano cohort study. Several studies have shown an association between air pollutants and hypertension via oxidative stress and inflammatory pathways. Yet, little is known about the modifying effects of nonchemical stressors on air pollutant risks for hypertension. The incidence of hypertension, a key risk factor for cardiovascular diseases (CVD), has been growing in the United States (U.S.) and CVD remains the leading cause of death among the U.S. Hispanic population. Novel methods for addressing interactions in a logistic regression context are being developed. We are also applying a community-based approach by involving the community in defining research questions, identifying mechanisms for becoming involved in research activities, and interpreting and disseminating research findings. This program will also help to identify culturally specific elements that could be used for an effective intervention in a Latino community to address disparities in air pollutant health risks.
Progress Summary:
There have been no modifications to the specific aims as stated in the original, competing application, although additional work has been conducted.
Aim 1: Develop new statistical methods that allow for a rigorous evaluation of interaction between chemical and non-chemical stressors in a logistic regression framework.
Under a logistic regression framework, we developed an analytic approach for evaluating interactions between binary and continuous independent variables, which are discretized using a quartile breakdown. We completed an R program for implementing the proposed estimation and testing methods. We conducted a simulation study for examining the interaction effect based on this method. The results are close to our targeted error probability and the power for detecting the interaction effect between two covariates increases with the absolute value of the interaction effect. We also examined the performance of our method when there are more than two covariates with a comparison to the generalized linear model with interaction. However, we found that the target error probabilities are influenced by the discretization of the continuous covariates. We re-worked the simulation to address this issue. We have also completed the application of these methods with a subset of the data that have been collected. We are now in process of writing the manuscript for submission.
In addition to the method that we proposed in the original grant application, we have also developed a novel concept of approaching interaction by borrowing the concept of “isobole” in toxicology (Sorensen et al., 2007) to define interaction in terms of a “statistical isobole.” We developed the estimation procedure; analytically examined some properties of the estimators; developed a test statistic for testing the interaction effect; and developed procedures to classify an isobole as having a synergistic or an antagonistic effect. Through intensive simulation, we have also calculated the power for interaction test using the statistical isobole. A manuscript describing this work was submitted for publication in the reporting period; revisions were required and the manuscript will be re-submitted by the end of the year.
Aim 2: Estimate exposure to psychosocial stressors and traffic-related and industrial pollutants.
Development of the questionnaire to assess exposures to psychosocial stressors. A paper describing the input received from the community in developing the final questionnaire regarding exposures to psychosocial stressors is in press (Symanski et al., 2015). The manuscript examines the engagement of Mexican-origin neighborhood residents in sharing their perspectives on environmental exposures, psychological stress and health consequences through their participation in focus groups, the establishment of the Neighborhood Council of Advisors (NCA) and interviews for the pilot questionnaire testing. This qualitative multi-level approach allowed for the collection of data that focused questions on the actual community experiences with chemical and non-chemical stressors. In conclusion, the mixed methods approach facilitated community involvement in the development of a culturally appropriate questionnaire that has been administered (interviewing was completed during the reporting period).
Administration of the questionnaire. The questionnaire was administered to 2,481 Mano a Mano cohort members who agreed to participate in our study. Table 1 summarizes demographic and lifestyle characteristics of the study population. A summary of the data on psychosocial factors appears in Table 2.
Table 1: Demographic and Lifestyle characteristics (N=2481)
N | (%) | OR | 95% CI | ||
---|---|---|---|---|---|
Age (years) | |||||
Mean (±SD) | 45.91 (12.67) | ||||
Range | 20-80 | ||||
< 30 | 241 | 9.71 | Ref | ||
30—39 | 641 | 25.84 | 2.656* | 1.647 | 4.282 |
40—49 | 634 | 25.55 | 7.576* | 4.756 | 12.07 |
50+ | 965 | 38.9 | 28.469* | 17.947 | 45.161 |
Gender | |||||
Men | 266 | 10.72 | Ref | ||
Women | 2215 | 89.28 | 0.749* | 0.58 | 0.966 |
Years of Education | |||||
<12 | 1493 | 60.18 | 1.203 | 0.978 | 1.48 |
High School Graduate or GED | 510 | 20.56 | 0.847 | 0.658 | 1.091 |
13+ | 477 | 19.23 | Ref | Ref | Ref |
Missing | 1 | 0.04 | N/A | ||
Nativity Status | |||||
United States | 516 | 20.8 | 2.206* | 1.808 | 2.691 |
Mexico | 1963 | 79.12 | Ref | Ref | Ref |
Other Country | 1 | 0.04 | >999.999 | <0.001 | >999.999 |
Missing | 1 | 0.04 | N/A | ||
Language of Interview | |||||
English | 448 | 18.06 | 0.979 | 0.797 | 1.202 |
Spanish | 2033 | 81.94 | Ref | ||
Years in the United States | |||||
Mean (±SD) | 24.78 (17.45) | ||||
Range | 1-80 | ||||
<10 | 461 | 18.68 | Ref | ||
10-19 | 764 | 30.96 | 1.8* | 1.382 | 2.345 |
20—29 | 401 | 16.25 | 3.227* | 2.408 | 4.326 |
30—39 | 352 | 14.26 | 5.772* | 4.249 | 7.84 |
40—49 | 198 | 8.02 | 6.833* | 4.739 | 9.852 |
50—59 | 141 | 5.71 | 9.003* | 5.864 | 13.823 |
60+ | 151 | 6.12 | 16.063* | 10.044 | 25.687 |
Degree of Acculturationⱡ | |||||
Score mean (±SD) | 2.20 (0.95) | ||||
Range | 0-4 | ||||
Low level of acculturation(BAS LE 2.50) | 1719 | 69.29 | Ref | ||
High level of acculturation(BAS > 2.50) | 762 | 30.71 | 1.475* | 1.242 | 1.75 |
*p<0.05 for associations between covariates and hypertension status |
Table 2: Psychosocial Factors
N | (%) | OR | 95% CI | ||
---|---|---|---|---|---|
Employment | |||||
Ever worked | 2051 | 82.67 | 0.931 | 0.752 | 1.154 |
Never worked | 403 | 16.24 | Ref | Ref | Ref |
Missing | 27 | 1.09 | N/A | ||
Income Level | |||||
< $25,000 | 769 | 31 | 1.789* | 1.419 | 2.255 |
$25,000 to $44,999 | 484 | 19.51 | Ref | Ref | Ref |
$45,000 to $74,999 | 242 | 9.75 | 0.891 | 0.646 | 1.228 |
Missing | 986 | 39.74 | N/A | ||
Smoking Status | |||||
Current | 169 | 6.81 | 1.206 | 0.88 | 1.652 |
Former | 343 | 13.83 | 2.12* | 1.675 | 2.682 |
Never | 1968 | 79.32 | Ref | ||
Missing | 1 | 0.04 | |||
Alcohol Use | |||||
Current | 373 | 15.03 | 1.079 | 0.864 | 1.349 |
Former | 208 | 8.38 | 2.08* | 1.549 | 2.793 |
Never | 1895 | 76.38 | REF | ||
Missing | 5 | 0.2 | N/A | ||
BMI | |||||
Underweight/Normal Weight (<24.9 kg/m2) | 351 | 14.15 | Ref | ||
Overweight (25.0 to 29.9 kg/m2) | 760 | 30.63 | 1.57* | 1.198 | 2.059 |
Obese I (30.0 to 34.9 kg/m2) | 662 | 26.68 | 2.088* | 1.587 | 2.749 |
Obese II (35.0 to 39.9 kg/m2) | 370 | 14.91 | 2.817* | 2.073 | 3.828 |
Obese III (≥40.0 kg/m2) | 266 | 10.72 | 5.966* | 4.198 | 8.479 |
Missing | 72 | 2.9 | N/A | ||
Asthma | |||||
Yes | 798 | 32.16 | 0.533* | 0.45 | 0.632 |
No | 1683 | 67.84 | Ref | ||
*p<0.05 for associations between covariates and hypertension status |
Air pollution exposure assessment. After excluding participants (n = 13) without valid geographic coordinates for residential addresses, the final sample size was N = 2,468. We obtained validated air pollution data for Ozone (O3) and particulate matter of aerodynamic diameter less than 2.5 micrometers (PM2.5) from the Texas Commission on Environmental Quality (TCEQ). Between 2008 and 2009, there were 48 active O3 monitoring stations and 13 active PM2.5 monitoring stations operated by TCEQ in the Houston-Galveston-Brazoria region. We calculated the maximum daily 8-hour running average for O3 and the mean 24-hour average for PM2.5 for every day in the study period from January 1, 2008 to December 31, 2013. Monitoring stations with 25% or more missing observations in a calendar year were excluded. Inverse Distance interpolation (IDW) with weight (p = 2) was used to calculate exposure estimates for each individual over the baseline year, using the three closest monitors to each participant’s geocoded residential address.
Aim 3. Examine interactions between air pollution and psychosocial stressors on prevalence of hypertension, with a focus on quantifying the modifying effects of nonchemical stressors on air pollutant effects.
Work on this aim did not begin during the reporting period.
Additional analyses.
We conducted a cross-sectional analysis of polycyclic aromatic hydrocarbons and diesel particulate matter exposures and hypertension among individuals of Mexican origin from the Mano a Mano cohort. Using geographical information systems, we linked modeled annual estimates of PAHs and diesel particulate matter at the census tract level from the 2002 and 2005 U.S. Environmental Protection Agency’s National-Scale Air Toxics Assessment to baseline residential addresses of cohort members who enrolled from 2001 to 2003 or 2004 to 2006, respectively. For each enrollment period, we applied mixed-effects logistic regression models to determine associations between diesel particulate matter and PAHs, separately, and self-reported hypertension while adjusting for confounders and the clustering of observations within census tracts and households. The study population consisted of 11,218 participants of which 77% were women. The mean participant age at baseline was 41 years. Following adjustment for age, there was a dose-dependent, positive association between PAHs and hypertension (medium exposure, adjusted odds ratio (OR) = 1.09, 95% CI: 0.88-1.36; high exposure, OR = 1.40, 95% CI: 1.01-1.94) for individuals enrolled during 2001-2003; associations were generally similar in magnitude, but less precise, following adjustment for age, gender, smoking, and BMI. No association was detected for the later period. There was no evidence of an association between residential levels of diesel particulate matter and hypertension.
Future Activities:
Using both traditional methods and the methods developed in the project, multiple logistic regression analyses will be applied to evaluate the modifying effects of neighborhood-based and individual-level psychosocial stressors that potentially affect susceptibility to hypertension due to air pollution. To account for pollutant source, we will conduct sensitivity analyses based on our two proximity measures.
The methodology paper for the concept that was proposed at AIM 1 of the project is almost complete and is expected to be submitted within 1 month. The “isobole” paper is in its final stage of data analysis and is expected to be submitted within 2 months.
References:
Sorensen, H., Cedergreen, N., Skovgaard, I, and Streibig, J. An Isobole-Based Statistical Model and Text for Synergism/Antagonism in Binary Mixture Toxicity Experiments, Environmental and Ecological Statistics, 2007;14(4):383-397.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
Other project views: | All 5 publications | 3 publications in selected types | All 3 journal articles |
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Type | Citation | ||
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Bangia KS, Symanski E, Strom SS, Bondy M. A cross-sectional analysis of polycyclic aromatic hydrocarbons and diesel particulate matter exposures and hypertension among individuals of Mexican origin. Environmental Health 2015;14:51. |
R834581 (2015) R834581 (Final) |
Exit Exit Exit |
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Symanski E, Karpman M, Jimenez M, Lopez DS, Felknor SA, Upadhyaya M, Strom SS, Bondy ML. Using a community-engaged approach to develop a bilingual survey about psychosocial stressors among individuals of Mexican origin. Journal of Health Care for the Poor and Underserved 2015;26(4):1456-1471. |
R834581 (2014) R834581 (2015) R834581 (Final) |
Exit Exit |
Supplemental Keywords:
Air pollution, epidemiology, exposure, sensitive populations, hypertension;, Health, Scientific Discipline, ENVIRONMENTAL MANAGEMENT, Risk Management, Health Risk Assessment, Risk Assessments, Biochemistry, Biology, cumulative exposure, cumulative risk, hypertension, air pollution, latino community, sensitive subjects, hispanics, cardiovascular disease, human health riskProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
- Final Report
- 2014 Progress Report
- 2013 Progress Report
- 2012 Progress Report
- 2011 Progress Report
- Original Abstract
3 journal articles for this project