Amy H. Auchincloss

A New Tool for Epidemiology: The Usefulness of Dynamic-Agent Models in Understanding Place Effects on Health

A major focus of recent work on the spatial patterning of health has been the study of how features of residential environments or neighborhoods may affect health. Place effects on health emerge from complex interdependent processes in which individuals interact with each other and their environment and in which both individuals and environments adapt and change over time. Traditional epidemiologic study designs and statistical regression approaches are unable to examine these dynamic processes. These limitations have constrained the types of questions asked, the answers received, and the hypotheses and theoretical explanations that are developed. Agent-based models and other systems-dynamics models may help to address some of these challenges. Agent-based models are computer representations of systems consisting of heterogeneous microentities that can interact and change/adapt over time in response to other agents and features of the environment. Using these models, one can observe how macroscale dynamics emerge from microscale interactions and adaptations. A number of challenges and limitations exist for agent-based modeling. Nevertheless, use of these dynamic models may complement traditional epidemiologic analyses and yield additional insights into the processes involved and the interventions that may be most useful.

Associations between Recent Exposure to Ambient Fine Particulate Matter and Blood Pressure in the Multi-Ethnic Study of Atherosclerosis (MESA)

Background Blood pressure (BP) may be implicated in associations observed between ambient particulate matter and cardiovascular morbidity and mortality. This study examined cross-sectional associations between short-term ambient fine particles (particulate matter ≤ 2.5 μm in aerodynamic diameter; PM2.5) and BP: systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse pressure (PP). Methods The study sample included 5,112 persons 45–84 years of age, free of cardiovascular disease at the Multi-Ethnic Study of Atherosclerosis baseline examination (2000–2002). Data from U.S. Environmental Protection Agency monitors were used to estimate ambient PM2.5 exposures for the preceding 1, 2, 7, 30, and 60 days. Roadway data were used to estimate local exposures to traffic-related particles. Results Results from linear regression found PP and SBP positively associated with PM2.5. For example, a 10-μg/m3 increase in PM2.5 30-day mean was associated with 1.12 mmHg higher pulse pressure [95% confidence interval (CI), 0.28–1.97] and 0.99 mmHg higher systolic BP (95% CI, –0.15 to 2.13), adjusted for age, sex, race/ethnicity, income, education, body mass index, diabetes, cigarette smoking and environmental tobacco smoke, alcohol use, physical activity, medications, atmospheric pressure, and temperature. Results were much weaker and not statistically significant for MAP and DBP. Although traffic-related variables were not themselves associated with BP, the association between PM2.5 and BP was stronger in the presence of higher traffic exposure. Conclusions Higher SBP and PP were associated with ambient levels of PM2.5 and the association was stronger in the presence of roadway traffic, suggesting that impairment of blood pressure regulation may play a role in response to air pollution.

Long-term Exposure to Ambient Particulate Matter and Prevalence of Subclinical Atherosclerosis in the Multi-Ethnic Study of Atherosclerosis

Exposure to airborne particulate matter has been linked to cardiovascular events. Whether this finding reflects an effect of particulate matter exposure on the triggering of events or development of atherosclerosis remains unknown. Using data from the Multi-Ethnic Study of Atherosclerosis collected at baseline (2000-2002), the authors investigated associations of 20-year exposures to particulate matter with measures of subclinical disease (coronary calcium, common carotid intimal-medial thickness, and ankle-brachial index) in 5,172 US adults without clinical cardiovascular disease. Particulate matter exposures for the 20 years prior to assessment of subclinical disease were obtained from a space-time model of Environmental Protection Agency monitor data linked to residential history data for each participant. Intimal-medial thickness was weakly, positively associated with exposures to particulate matter <10 microm in aerodynamic diameter and <2.5 microm in aerodynamic diameter after controlling for age, sex, race/ethnicity, socioeconomic factors, diet, smoking, physical activity, blood lipids, diabetes, hypertension, and body mass index (1-4% increase per 21-microg/m(3) increase in particulate matter <10 microm in aerodynamic diameter or a 12.5-microg/m(3) increase in particulate matter <2.5 microm in aerodynamic diameter). No consistent associations with other measures of atherosclerosis were observed. There was no evidence of effect modification by sociodemographic factors, lipid status, smoking, diabetes, body mass index, or site. Results are compatible with some effect of particulate matter exposures on development of carotid atherosclerosis.

Filling the Gaps: Spatial Interpolation of Residential Survey Data in the Estimation of Neighborhood Characteristics

The measurement of area-level attributes remains a major challenge in studies of neighborhood health effects. Even when neighborhood survey data are collected, they necessarily have incomplete spatial coverage. We investigated whether interpolation of neighborhood survey data was aided by information on spatial dependencies and supplementary data. Neighborhood “availability of healthy foods” was measured in a population-based survey of 5186 persons in Baltimore, New York, and Forsyth County (North Carolina). The following supplementary data were compiled from Census 2000 and InfoUSA, Inc.: distance to supermarkets, density of supermarkets and fruit and vegetable stores, housing density, distance to a high-income area, and percent of households that do not own a vehicle. We compared 4 interpolation models (ordinary least squares, residual kriging, spatial error regression, and thin-plate splines) using error statistics and Pearson correlation coefficients (r) from repeated replications of cross-validations. There was positive spatial autocorrelation in neighborhood availability of healthy foods (by site, Moran coefficient range = 0.10–0.28; all P < 0.0001). Prediction performances were generally similar for the evaluated models (r ≈ 0.35 for Baltimore and Forsyth; r ≈ 0.54 for New York). Supplementary data accounted for much of the spatial autocorrelation and, thus, spatial modeling was only advantageous when spatial correlation was at least moderate. A variety of interpolation techniques will likely need to be utilized in order to increase the data available for examining health effects of residential environments. The most appropriate method will vary depending on the construct of interest, availability of relevant supplementary data, and types of observed spatial patterns.

Long-term exposure to airborne particles and arterial stiffness: the Multi-Ethnic Study of Atherosclerosis (MESA).

Background Increased arterial stiffness could represent an intermediate subclinical outcome in the mechanistic pathway underlying associations between average long-term pollution exposure and cardiovascular events. Objective We hypothesized that 20 years of exposure to particulate matter (PM) ≤ 2.5 and 10 μm in aerodynamic diameter (PM2.5 and PM10, respectively) would be positively associated with arterial stiffness in 3,996 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) who were seen at six U.S. study sites. Methods We assigned pollution exposure during two decades preceding a clinical exam (2000–2002) using observed PM10 from monitors nearest participants’ residences and PM10 and PM2.5 imputed from a space-time model. We examined three log-transformed arterial stiffness outcome measures: Young’s modulus (YM) from carotid artery ultrasound and large (C1) and small (C2) artery vessel compliance from the radial artery pulse wave. All associations are expressed per 10 μg/m3 increment in PM and were adjusted for weather, age, sex, race, glucose, triglycerides, diabetes, waist:hip ratio, seated mean arterial pressure, smoking status, pack-years, cigarettes per day, environmental tobacco smoke, and physical activity. C1 and C2 models were further adjusted for heart rate, weight, and height. Results Long-term average particle exposure was not associated with greater arterial stiffness measured by YM, C1, or C2, and the few associations observed were not robust across metrics and adjustment schemes. Conclusions Long-term particle mass exposure did not appear to be associated with greater arterial stiffness in this study sample.

Airborne particulate matter exposure and urinary albumin excretion: the Multi-Ethnic Study of Atherosclerosis.

Objectives: Understanding mechanistic pathways linking airborne particle exposure to cardiovascular health is important for causal inference and setting environmental standards. We evaluated whether urinary albumin excretion, a subclinical marker of microvascular function which predicts cardiovascular events, was associated with ambient particle exposure. Methods: Urinary albumin and creatinine were measured among members of the Multi-Ethnic Study of Atherosclerosis at three visits during 2000–2004. Exposure to PM2.5 and PM10 (μg/m3) was estimated from ambient monitors for 1 month, 2 months and two decades before visit one. We regressed recent and chronic (20 year) particulate matter (PM) exposure on urinary albumin/creatinine ratio (UACR, mg/g) and microalbuminuria at first examination, controlling for age, race/ethnicity, sex, smoking, second-hand smoke exposure, body mass index and dietary protein (nu200a=u200a3901). We also evaluated UACR changes and development of microalbuminuria between the first, and second and third visits which took place at 1.5- to 2-year intervals in relation to chronic PM exposure prior to baseline using mixed models. Results: Chronic and recent particle exposures were not associated with current UACR or microalbuminuria (per 10 μg/m3 increment of chronic PM10 exposure, mean difference in log UACRu200a=u200a−0.02 (95% CI −0.07 to 0.03) and relative probability of having microalbuminuriau200a=u200a0.92 (95% CI 0.77 to 1.08)) We found only weak evidence that albuminuria was accelerated among those chronically exposed to particles: each 10 μg/m3 increment in chronic PM10 exposure was associated with a 1.14 relative probability of developing microalbuminuria over 3–4 years, although 95% confidence intervals included the null (95% CI 0.96 to 1.36). Conclusions: UACR is not a strong mechanistic marker for the possible influence of air pollution on cardiovascular health in this sample.