Susan Hurley

Post office box addresses: a challenge for geographic information system-based studies.

Background Geographic information system (GIS)-based health studies require information on the physical location of data points, such as subject addresses. In a study of California women diagnosed with breast cancer between 1988 and 1997, we needed to locate the residential addresses of 4,537 women with post office boxes (POBs) Methods We investigated the feasibility of tracing street addresses for the POBs and examined potential selection biases and case attribute misclassifications introduced by different methods of handling POBs in GIS-based health studies. Results Our tracing method yielded street addresses for only 34% of POBs in our study. Examination of subjects’ case characteristics revealed that boxholders were not representative of the full population. Geocoding using a POB’s delivery-weighted five-digit zip code centroid, as a proxy for street address, resulted in case attribute misclassification for 81% of boxholders. Conclusions Disease registries should modernize their infrastructure to complement GIS technologies. Epidemiologists should understand GIS data limitations and consider potential biases introduced by incomplete or inaccurate geocoding.

Estimating exposure to polycyclic aromatic hydrocarbons: A comparison of survey, biological monitoring, and geographic information system-based methods

Our objective was to compare polycyclic aromatic hydrocarbon (PAH) exposure estimates based on survey, biological monitoring, and geographic information system (GIS) methods. The 304 participants in this study supplied a urine sample and completed questionnaires about exposure to potential PAH sources. We assayed urine samples for 1-hydroxypyrene-O-glucuronide (1-OHPG), the major metabolite of pyrene, a common PAH. We used a GIS to estimate traffic exhaust exposure using vehicle count data at the residence and workplace. The five subjects who reported smoking during the 48-hour period had median 1-OHPG concentrations 10-fold that of nonsmokers (1.6 versus 0.16 pmol/mL; P = 0.01). Among nonsmokers, those who reported eating grilled, roasted, or broiled meat had significantly higher 1-OHPG concentrations than those who did not reported eating meat prepared by these methods (0.25 versus 0.06 pmol/mL; P = 0.02). Nonsmokers who reported traveling on roads for ≥3 hours during the 48-hour period also had significantly higher 1-OHPG levels than those who traveled <3 hours (0.23 versus 0.11 pmol/mL; P = 0.03). 1-OHPG levels were also correlated with hours of secondhand smoke exposure among nonsmokers (P = 0.04). In this study, 1-OHPG urine concentrations were not associated with self-reported exposures to cooking smoke, wood burning, or traffic levels near the home or to traffic density or urban/rural status determined using a GIS. Self-reported indicators of residential proximity to high traffic volume were, however, associated with GIS traffic density measures. (Cancer Epidemiol Biomarkers Prev 2006;15(7):1376–81)

High concentrations of polybrominated diphenylethers (PBDEs) in breast adipose tissue of California women.

We measured major PBDEs and PCBs in breast adipose tissues of California women participating in a breast cancer study in the late 1990s. Samples were analyzed using gas chromatography with electron impact ionization and tandem mass spectrometry detection. The congener profile observed was: BDE47>BDE99>BDE153>BDE100>BDE154 and PCB153>PCB180>PCB138>PCB118. Whereas high correlations were observed within each chemical class, very weak correlations appeared between classes, pointing to different exposure pathways. Weak negative associations were observed for PBDE congeners and age. Our PBDE data are among the highest reported, exceeding data from the National Health and Nutrition Examination Survey and consistent with the high use of PBDEs in California. These data may be helpful in establishing a baseline for PBDE body burdens to gauge changes over time as a result of restrictions in the use of PBDE formulations.

Residential proximity to agricultural pesticide use and incidence of breast cancer in California, 1988-1997.

California is the largest agricultural state in the United States and home to some of the world’s highest breast cancer rates. The objective of our study was to evaluate whether California breast cancer rates were elevated in areas with recent high agricultural pesticide use. We identified population-based invasive breast cancer cases from the California Cancer Registry for 1988–1997. We used California’s pesticide use reporting data to select pesticides for analysis based on use volume, carcinogenic potential, and exposure potential. Using 1990 and 2000 U.S. Census data, we derived age- and race-specific population counts for the time period of interest. We used a geographic information system to aggregate cases, population counts, and pesticide use data for all block groups in the state. To evaluate whether breast cancer rates were related to recent agricultural pesticide use, we computed rate ratios and 95% confidence intervals using Poisson regression models, adjusting for age, race/ethnicity, and neighborhood socioeconomic status and urbanization. This ecologic (aggregative) analysis included 176,302 invasive breast cancer cases and 70,968,598 person-years of observation. The rate ratios did not significantly differ from 1 for any of the selected pesticide categories or individual agents. The results from this study provide no evidence that California women living in areas of recent, high agricultural pesticide use experience higher rates of breast cancer.

The Association Between Neighborhood Characteristics and Body Size and Physical Activity in the California Teachers Study Cohort

OBJECTIVES We considered interactions between physical activity and body mass index (BMI) and neighborhood factors. METHODS We used recursive partitioning to identify predictors of low recreational physical activity (< 2.5 hours/week) and overweight and obesity (BMI ≥ 25.0 kg/m(2)) among 118,315 women in the California Teachers Study. Neighborhood characteristics were based on 2000 US Census data and Reference US business listings. RESULTS Low physical activity and being overweight or obese were associated with individual sociodemographic characteristics, including race/ethnicity and age. Among White women aged 36 to 75 years, living in neighborhoods with more household crowding was associated with a higher probability of low physical activity (54% vs 45% to 51%). In less crowded neighborhoods where more people worked outside the home, the existence of fewer neighborhood amenities was associated with a higher probability of low physical activity (51% vs 46%). Among non-African American middle-aged women, living in neighborhoods with a lower socioeconomic status was associated with a higher probability of being overweight or obese (46% to 59% vs 38% in high-socioeconomic status neighborhoods). CONCLUSIONS Associations between physical activity, overweight and obesity, and the built environment varied by sociodemographic characteristics in this educated population.

Effects of marital status and economic resources on survival after cancer: A population-based study.

Although married cancer patients have more favorable survival than unmarried patients, reasons underlying this association are not fully understood. The authors evaluated the role of economic resources, including health insurance status and neighborhood socioeconomic status (nSES), in a large California cohort.

Differences in marital status and mortality by race/ethnicity and nativity among California cancer patients

It has been observed that married cancer patients have lower mortality rates than unmarried patients, but data for different racial/ethnic groups are scarce. The authors examined the risk of overall mortality associated with marital status across racial/ethnic groups and sex in data from the California Cancer Registry.

Adipose levels of dioxins and risk of breast cancer

Objective: Our objective was to evaluate the breast cancer risk associated with body burden levels of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs).Methods: We conducted a hospital-based case-control study among 79 women diagnosed with invasive breast cancer and 52 controls diagnosed with benign breast conditions. We collected breast adipose tissue and analyzed it for all 17 2,3,7,8-substitituted PCDD/PCDFs. We used unconditional logistic regression to calculate age- and race-adjusted exposure-specific odds ratios (ORs) and 95% confidence intervals (CI) for each individual PCDD/PCDF congener as well as for the summary measures (I-TEQ, Adj-TEQ).Results: Dioxin levels were consistent with reports from other small, contemporary studies of body burdens in the U.S. None of the odds ratios for any of the congeners or summary measures differed significantly from one. Especially for the PCDF congeners, point estimates tended to be below one. One notable exception was octachlorodibenzo-p-dioxin (OCDD), for which the odds ratio for the second and third tertiles appeared modestly elevated (OR = 1.22, 95% CI: 0.47:3.16 and OR = 1.62, 95% CI: 0.64:4.12, respectively), though the test for trend was not significant (p = 0.36).Conclusion: Breast cancer risk was not associated with adipose levels of PCDD/PCDFs. More study is suggested among women of color who may have higher body burden levels of these compounds.

A cross-sectional analysis of light at night, neighborhood sociodemographics and urinary 6-sulfatoxymelatonin concentrations: implications for the conduct of health studies

BackgroundThere is accumulating evidence that circadian disruption, mediated by alterations in melatonin levels, may play an etiologic role in a wide variety of diseases. The degree to which light-at-night (LAN) and other factors can alter melatonin levels is not well-documented. Our primary objective was to evaluate the degree to which estimates of outdoor environmental LAN predict 6-sulftoxymelatonin (aMT6s), the primary urinary metabolite of melatonin. We also evaluated other potential behavioral, sociodemographic, and anthropomorphic predictors of aMT6s.MethodsStudy participants consisted of 303 members of the California Teachers Study who provided a 24-hour urine specimen and completed a self-administered questionnaire in 2000. Urinary aMT6s was measured using the Bühlmann ELISA. Outdoor LAN levels were estimated from satellite imagery data obtained from the U.S. Defense Meteorological Satellite Program’s (DMSP) Operational Linescan System and assigned to study participants’ geocoded residential address. Information on other potential predictors of aMT6s was derived from self-administered surveys. Neighborhood socioeconomic status (SES) was based on U.S. Census block group data.ResultsLower aMT6s levels were significantly associated with older age, shorter nights, and residential locations in lower SES neighborhoods. Outdoor sources of LAN estimated using low-dynamic range DMSP data had insufficient variability across urban neighborhoods to evaluate. While high-dynamic range DMSP offered much better variability, it was not significantly associated with urinary aMT6s.ConclusionsFuture health studies should utilize the high-dynamic range DMSP data and should consider other potential sources of circadian disruption associated with living in lower SES neighborhoods.

Evaluation of the agreement between modeled and monitored ambient hazardous air pollutants in California

Elevated breast cancer incidence rates in urban areas have led to speculation regarding the potential role of air pollution. In order to inform the exposure assessment for a subsequent breast cancer study, we evaluated agreement between modeled and monitored hazardous air pollutants (HAPs). Modeled annual ambient concentrations of HAPs in California came from the US Environmental Protection Agency’s National Air Toxics Assessment database for 1996, 1999, 2002, and 2005 and corresponding monitored data from the California Air Resources Board’s air quality monitoring program. We selected 12 compounds of interest for our study and focused on evaluating agreement between modeled and monitored data, and of temporal trends. Modeled data generally underestimated the monitored data, especially in 1996. For most compounds agreement between modeled and monitored concentrations improved over time. We concluded that 2002 and 2005 modeled data agree best with monitored data and are the most appropriate years for direct use in our subsequent epidemiologic analysis.