Carolyn G. Scrafford

Dietary flavonoid intake and risk of cancer in postmenopausal women: The Iowa Women's Health Study

Flavonoids, which are found in certain plant foods, are thought to lower cancer risk through their antioxidant, antiestrogenic and antiproliferative properties. We examined the association of intake of total flavonoids and 7 flavonoid subclasses with risk of lung, colorectal, breast, pancreatic and upper aerodigestive cancer among women in a large prospective cohort study. Study participants were 34,708 postmenopausal women in the Iowa Womens Health Study who completed a food frequency questionnaire and were followed for cancer occurrence from 1986 through 2004. Flavonoid intake was estimated from 3 databases developed by the USDA Nutrient Data Laboratory (NDL). Hazard ratios (HR) for cancer risk were calculated across total flavonoid and flavonoid subclass intake categories. Interactions between smoking history and flavonoid intake were also examined. After multivariable adjustment, lung cancer incidence was inversely associated with intakes of flavanones (HR = 0.68; 95% CI: 0.53–0.86, all results highest vs. lowest quintile) and proanthocyanidins (HR = 0.75; 95% CI: 0.57–0.97). Among current and past smokers, those with intakes in the highest quintile for flavanones (HR = 0.66; 95% CI: 0.50–0.86), and proanthocyanidins (HR = 0.66; 95% CI; 0.49–0.89) had significantly lower lung cancer incidence than those in the lowest quintile. Similar associations were not seen in never smokers. Isoflavone intake was inversely associated with overall cancer incidence (HR = 0.93, 95% CI: 0.86–1.00). This study provides further support for a beneficial effect of flavonoid intake on lung cancer risk, especially among current and past smokers.

Exposure data for cosmetic products: Facial cleanser, hair conditioner, and eye shadow

Reliable exposure information for cosmetic and other personal care products and ingredients is needed in order to conduct safety assessments. Essential information includes both the amount of product applied, and the frequency of use. To obtain current data, a study to assess consumer use practices was undertaken. Three widely used types of cosmetic products - facial cleanser, hair conditioner, and eye shadow - were included in the study. Three hundred and sixty women, ages 18-69 years, who regularly use the products of interest, were recruited nationwide within the US. Subjects were provided with a new container of the brand of product they normally use and kept diaries and recorded detailed daily usage information over a two week period. Products were weighed at the start and completion of the study in order to determine the total amount of product used. Statistical analyses of the data were conducted to derive summary distributions of use patterns. The mean and median usage per application, respectively, for the three product types were: facial cleanser, 2.57 g and 2.11 g; hair conditioner, 13.13 g and 10.21 g; and eye shadow, 0.03 g and 0.009 g. The mean and median usage per day for the three product types was: facial cleanser, 4.06 g and 3.25 g; hair conditioner, 13.77 g and 10.62 g; and eye shadow, 0.04 g and 0.010 g. The mean number of applications per day for facial cleanser, hair conditioner, and eye shadow was 1.6, 1.1, and 1.2, respectively. This study provides an estimate of current exposure information for commonly used products which will be useful for risk assessment purposes.

Egg consumption and cardiovascular disease among diabetic individuals: a systematic review of the literature.

Background This study reviewed epidemiological and experimental evidence on the relationship between egg consumption and cardiovascular disease (CVD) risks among type II diabetes mellitus (T2DM) individuals, and T2DM risk in nondiabetic subjects. Results Four of the six studies that examined CVD and mortality and egg consumption among diabetics found a statistically significant association. Of the eight studies evaluating incident T2DM and egg consumption, four prospective studies found a statistically significant association. Lack of adjustment for dietary confounders was a common study limitation. A small number of experimental studies examined the relationship between egg intake and CVD risk biomarkers among diabetics or individuals with T2DM risk factors. Studies among healthy subjects found suggestive evidence that dietary interventions that include eggs may reduce the risk of T2DM and metabolic syndrome. Conclusion Differences in study design, T2DM status, exposure measurement, subject age, control for confounders and follow-up time present significant challenges for conducting a meta-analysis. Conflicting results, coupled with small sample sizes, prevent broad interpretation. Given the study limitations, these findings need to be further investigated.

Factors that Influence the Radiofrequency Power Output of GSM Mobile Phones

Abstract Erdreich, L. S., Van Kerkhove, M. D., Scrafford, C. G., Barraj, L., McNeely, M., Shum, M., Sheppard, A. R. and Kelsh, M. Factors that Influence the Radiofrequency Power Output of GSM Mobile Phones. Radiat. Res. 168, 253–261 (2007). Epidemiological studies of mobile phone use and risk of brain cancer have relied on self-reported use, years as a subscriber, and billing records as exposure surrogates without addressing the level of radiofrequency (RF) power output. The objective of this study was to measure environmental, behavioral and engineering factors affecting the RF power output of GSM mobile phones during operation. We estimated the RF-field exposure of volunteer subjects who made mobile phone calls using software-modified phones (SMPs) that recorded output power settings. Subjects recruited from three geographic areas in the U.S. were instructed to log information (place, time, etc.) for each call made and received during a 5-day period. The largest factor affecting energy output was study area, followed by user movement and location (inside or outside), use of a hands-free device, and urbanicity, although the two latter factors accounted for trivial parts of overall variance. Although some highly statistically significant differences were identified, the effects on average energy output rate were usually less than 50% and were generally comparable to the standard deviation. These results provide information applicable to improving the precision of exposure metrics for epidemiological studies of GSM mobile phones and may have broader application for other mobile phone systems and geographic locations.

Evaluation of Exposure to Arsenic in Residential Soil

In response to concerns regarding arsenic in soil from a pesticide manufacturing plant, we conducted a biomonitoring study on children younger than 7 years of age, the age category of children most exposed to soil. Urine samples from 77 children (47% participation rate) were analyzed for total arsenic and arsenic species related to ingestion of inorganic arsenic. Older individuals also provided urine (n = 362) and toenail (n = 67) samples. Speciated urinary arsenic levels were similar between children (geometric mean, geometric SD, and range: 4.0, 2.2, and 0.89–17.7 μg/L, respectively) and older participants (3.8, 1.9, 0.91–19.9 μg/L) and consistent with unexposed populations. Toenail samples were < 1 mg/kg. Correlations between speciated urinary arsenic and arsenic in soil (r = 0.137, p = 0.39; n = 41) or house dust (r = 0.049, p = 0.73; n = 52) were not significant for children. Similarly, questionnaire responses indicating soil exposure were not associated with increased urinary arsenic levels. Relatively low soil arsenic exposure likely precluded quantification of arsenic exposure above background.

Perchlorate exposure from food crops produced in the lower Colorado River region.

The Colorado River shows low levels of perchlorate derived from aerospace- and defense-related fuel industries once located near the Las Vegas Wash. At sufficiently high dosages perchlorate can disrupt thyroid function by inhibiting uptake of iodide. The Colorado River is the primary source of irrigation water for most food crops grown in Southern California and Southwestern Arizona. The objective of this study was to evaluate potential perchlorate exposure from food crops produced in the lower Colorado River region (LCRR). The major food commodities produced in the region were sampled and perchlorate levels were determined by ion chromatography followed by detection using either conductivity or tandem mass spectrometry, depending on analyte levels. The Monte Carlo module of the Dietary Exposure Evaluation Model (DEEM™) was used to derive an estimate of the 2-day average perchlorate intakes. Data were derived assuming that individuals residing in the LCRR get their fruits and vegetables from within the LCRR as well as from other areas in the United States, or assuming individuals living in the LCRR get their fruits and vegetables from the LCRR only. Perchlorate exposure estimates derived in this study are comparable to exploratory estimates by the US Food and Drug Administration. For infants and children, over 50% of the estimated perchlorate exposure was from milk. The relative impact of vegetables and fruit toward perchlorate exposure increased by age through adulthood. Cumulative perchlorate exposure estimates based on this hypothetical analysis could approach or exceed the NAS reference dose (RfD) for some population groups as drinking water levels exceeded 6 μg/l. However, few individuals are exposed to perchlorate in drinking water at levels above 4 μg/l in the United States and very few would be exposed to perchlorate levels exceeding the RfD, whether consuming food crops from within or outside the LCRR.

Within-day drinking water consumption patterns: Results from a drinking water consumption survey

Data currently available on drinking water intakes do not support dietary exposure estimates for contaminants that have acute effects lasting less than 24 h. Realistic exposure estimates for these types of contaminants in drinking water require detailed information on amounts and time of consumption for each drinking occasion during a day. A nationwide water consumption survey was conducted to address how often, when, and how much water is consumed at specific times during the day. The survey was conducted in two waves, to represent two seasons, and the survey instrument consisted of 7-day water consumption diaries. Data on total daily amounts consumed, number of drinking occasions per day, amounts consumed per drinking occasion, and intervals between drinking occasions show larger between-subjects variation than within-subject variation. Statistically significant associations were also observed between drinking water consumption patterns and participants’ ages and sex and geographical regions in which these participants live. The number of drinking occasions on a given day varied from 0 to 19, with the majority of respondents reporting 6 or less drinking occasions per day. The average interval between drinking occasions varied from 1 to 17 h, with 57% of the person-days reporting average intervals at least 3 h apart. The mean amount consumed per drinking occasion showed little association with the number of drinking occasions and fluctuated between 8 and 10 oz. To our knowledge, this survey is the only source of information on within-day patterns (i.e., when and how much) of drinking water consumption for a nationally representative sample of the US population. The detailed water consumption data from this survey can be used to support less than 24-h dietary exposure estimates for contaminants in drinking water.

Arsenic levels in wipe samples collected from play structures constructed with CCA-treated wood : Impact on exposure estimates

Lumber treated with chromated copper arsenate (CCA) has been used in residential outdoor wood structures and playgrounds. The U.S. EPA has conducted a probabilistic assessment of childrens exposure to arsenic from CCA-treated structures using the Stochastic Human Exposure and Dose Simulation model for the wood preservative scenario (SHEDS-Wood). The EPA assessment relied on data from an experimental study using adult volunteers and designed to measure arsenic in maximum hand and wipe loadings. Analyses using arsenic handloading data from a study of children playing on CCA-treated play structures in Edmonton, Canada, indicate that the maximum handloading values significantly overestimate the exposure that occurs during actual play. The objective of our paper is to assess whether the dislodgeable arsenic residues from structures in the Edmonton study are comparable to those observed in other studies and whether they support the conclusion that the values derived by EPA using modeled maximum loading values overestimate hand exposures. We compared dislodgeable arsenic residue data from structures in the playgrounds in the Edmonton study to levels observed in studies used in EPAs assessment. Our analysis showed that the dislodgeable arsenic levels in the Edmonton playground structures are similar to those in the studies used by EPA. Hence, the exposure estimates derived using the handloading data from children playing on CCA-treated structures are more representative of childrens actual exposures than the overestimates derived by EPA using modeled maximum values. Handloading data from children playing on CCA-treated structures should be used to reduce the uncertainty of modeled estimates derived using the SHEDS-Wood model.

The SHEDS-Wood Model: Incorporation of Observational Data to Estimate Exposure to Arsenic for Children Playing on CCA-Treated Wood Structures

Background Lumber treated with chromated copper arsenate (CCA) compounds has been used in residential outdoor wood structures and public playgrounds. The U.S. Environmental Protection Agency (EPA) has conducted a probabilistic assessment of children’s exposure to arsenic using the Stochastic Human Exposure and Dose Simulation model for the wood preservative scenario (SHEDS-Wood). The assessment relied on data derived from an experimental study conducted using adult volunteers and designed to result in maximum hand and wipe loadings to estimate the residue–skin transfer efficiency. Recent analyses of arsenic hand-loading data generated by studies of children actively involved in playing on CCA-treated structures indicate that the transfer efficiency coefficient and hand-loading estimates derived from the experimental study significantly overestimate the amount that occurs during actual play. Objectives Our goal was to assess the feasibility of using child hand-loading data in the SHEDS-Wood model and their impact on exposure estimates. Methods We used data generated by the larger of the studies of children in SHEDS-Wood, instead of the distributions used by U.S. EPA. We compared our estimates of the lifetime average daily dose (LADD) and average daily dose (ADD) with those derived by the U.S. EPA. Results Our analysis indicates that data from observational studies of children can be used in SHEDS-Wood. Our estimates of the mean (and 95th percentile) LADD and ADD were 27% (10%) and 29% (15%) of the estimates derived by U.S. EPA. Conclusion We recommend that the SHEDS-Woods model use data from studies of children actively playing on playsets to more accurately estimate children’s actual exposures to CCA.

Partitioning of Dietary Metal Intake—A Metal Dietary Exposure Screening Tool

Detection of heavy metals at trace or higher levels in foods and food ingredients is not unexpected given the widespread unavoidable presence of several metals in nature, coupled with advancement in analytical methods and lowering limits of detection. To assist risk managers with a rapid risk assessment when facing these situations, a metal dietary exposure screening tool (MDEST) was developed. The tool uses food intake rates based on the National Health and Nutrition Examination Survey 2005-2010 consumption data for the U.S. population two+ years and up and for infants age six months to <two years based on the Nestlé Feeding Infants and Toddlers Study, and existing exposure limits for several frequently detected metals (e.g., inorganic arsenic, cadmium, chromium, lead, and mercury). The tool has data entry fields for detected concentrations and includes algorithms that combine metal levels with consumption data to generate screening-level exposure estimates, which it then compares to MDEST assigned default portions of the exposure limits in the risk characterization module. As a screening-level tool, the risk assessment output is intentionally conservative, public health protective, and useful for a rapid assessment to set aside issues that are not of concern. Issues that cannot be readily resolved using this screening tool will need to be further evaluated with more refined input data that are tailored to the specific question or situation under consideration.