Biomedical subjects

D Mage

Publications and source records attributed to D Mage.

5 recordsLinked to original sources

PubMed2000

Predicting particulate (PM10) personal exposure distributions using a random component superposition statistical model.

This paper presents a new statistical model designed to extend our understanding from prior personal exposure field measurements of urban populations to other cities where ambient monitoring data, but no personal exposure measurements, exist. The model partitions personal exposure into two distinct components: ambient concentration and nonambient concentration. It is assumed the ambient and nonambient concentration components are uncorrelated and add together; therefore, the model is called a random component superposition (RCS) model. The 24-hr ambient outdoor concentration is multiplied by a dimensionless "attenuation factor" between 0 and 1 to account for deposition of particles as the ambient air infiltrates indoors. The RCS model is applied to field PM10 measurement data from three large-scale personal exposure field studies: THEES (Total Human Environmental Exposure Study) in Phillipsburg, NJ; PTEAM (Particle Total Exposure Assessment Methodology) in Riverside, CA; and the Ethyl Corporation study in Toronto, Canada. Because indoor sources and activities (smoking, cooking, cleaning, the personal cloud, etc.) may be similar in similar populations, it was hypothesized that the statistical distribution of nonambient personal exposure is invariant across cities. Using a fixed 24-hr attenuation factor as a first approximation derived from regression analysis for the respondents, the distributions of nonambient PM10 personal exposures were obtained for each city. Although the mean ambient PM10 concentrations in the three cities varied from 27.9 micrograms/m3 in Toronto to 60.9 micrograms/m3 in Phillipsburg to 94.1 micrograms/m3 in Riverside, the mean nonambient components of personal exposures were found to be closer: 52.6 micrograms/m3 in Toronto; 52.4 micrograms/m3 in Phillipsburg; and 59.2 micrograms/m3 in Riverside. The three frequency distributions of the nonambient components of exposure also were similar in shape, giving support to the hypothesis that nonambient concentrations are similar across different cities and populations. These results indicate that, if the ambient concentrations were completely controlled and set to zero in all three cities, the median of the remaining personal exposures to PM10 would range from 32.0 micrograms/m3 (Toronto) to 34.4 micrograms/m3 (Phillipsburg) to 48.8 micrograms/m3 (Riverside). The highest-exposed 30% of the population in the three cities would still be exposed to 24-hr average PM10 concentrations of 47-74 micrograms/m3; the highest 20% would be exposed to concentrations of 56-92 micrograms/m3; the highest 10% to concentrations of 88-131 micrograms/m3; and the highest 5% to 133-175 micrograms/m3, due only to indoor sources and activities. The distribution for the difference between personal exposures and indoor concentrations, or the "personal cloud," also was similar in the three cities, with a mean of 30-35 micrograms/m3, suggesting that the personal cloud accounts for more than half of the nonambient component of PM10 personal exposure in the three cities. Using only the ambient measurements in Toronto, the nonambient data from THEES in Phillipsburg was used to predict the entire personal exposure distribution in Toronto. The PM10 exposure distribution predicted by the model showed reasonable agreement with the PM10 personal exposure distribution measured in Toronto. These initial results suggest that the RCS model may be a powerful tool for predicting personal exposure distributions and statistics in other cities where only ambient particle data are available.

Air Pollution↗

PubMed1999

Assessment of human exposure to ambient particulate matter.

Recent epidemiological studies have consistently shown that the acute mortality effects of high concentrations of ambient particulate matter (PM), documented in historic air pollution episodes, may also be occurring at the low to moderate concentrations of ambient PM found in modern urban areas. In London in December 1952, the unexpected deaths due to PM exposure could be identified and counted as integers by the coroners. In modern times, the PM-related deaths cannot be as readily identified, and they can only be inferred as fractional average daily increases in mortality rates using sophisticated statistical filtering and analyses of the air quality and mortality data. The causality of the relationship between exposure to ambient PM and acute mortality at these lower modern PM concentrations has been questioned because of a perception that there is little significant correlation in time between the ambient PM concentrations and measured personal exposure to PM from all sources (ambient PM plus indoor-generated PM). This article shows that the critical factor supporting the plausibility of a linear PM mortality relationship is the expected high correlation in time of people's exposure to PM of ambient origin with measured ambient PM concentrations, as used in the epidemiological time series studies. The presence of indoor and personal sources of PM masks this underlying relationship, leading to confusion in the scientific literature about the strong underlying temporal relationship between personal exposure to PM of ambient origin and ambient PM concentration. The authors show that the sources of PM of non-ambient origin operate independently of the ambient PM concentrations, so that the mortality effect of non-ambient PM, if any, must be independent of the effects of the ambient PM exposures.

Air Pollutants, Occupational↗

PubMed1998

Factors associated with self-reported, pesticide-related visits to health care providers in the agricultural health study.

To investigate factors associated with pesticide-related visits to health care providers (i.e., doctor or hospital visits), responses to self-administered questionnaires received from 35,879 licensed restricted-use pesticide applicators participating in the Agricultural Health Study were analyzed. (In Iowa, applicators are actually certified, whereas in North Carolina they are licensed; for ease of reference, the term license will be used for both states in this paper.) The cohort reported a total of more than 10.9 million pesticide-application days. These applications were associated with one or more pesticide-related health care visits by 2,214 applicators (7.0% of the applicator cohort for whom health care visit data were available). The odds of a pesticide-related health care visit were increased for commercial applicators compared to private applicators [odds ratio (OR = 1.77; 95% confidence interval (CI), 1.52-2.06) and for applicators who used insecticides 70 times or more in their lifetime compared to those who used insecticides less frequently (OR = 1.43; CI, 1.26-1.63). After adjusting for the number of applications in a logistic regression model, significantly higher odds of health care visits were observed among North Carolina applicators compared to Iowa applicators (OR = 1.35; CI, 1.17-1.52), among applicators who mixed their own pesticides (OR = 1.65; CI, 1. 22-2.23), and among applicators who personally repaired their pesticide application equipment at least once per year (OR = 1.12; CI, 1.06-1.25). Significantly lower odds were found among female versus male applicators (OR = 0.68; CI, 0.46-0.99) and among applicators who graduated from high school versus those who did not (OR = 0.82; CI, 0.71-0.94 for high school graduates and OR = 0.79; CI, 0.68-0.91 for those with at least some college). Several methods of pesticide application to crops, seed, or stored grain were also associated with significantly elevated odds ratios of health care visits. These observations suggest that several steps can be taken to reduce the number of health care visits resulting from occupational exposure to pesticides. The implications of this pattern of pesticide-related health care visits may have etiologic implications for cancer and other chronic diseases.

Adult↗

PubMed1991

A comparison of the direct and indirect methods of human exposure.

Surveys of human exposures to pollutants that incorporate biological measures of exposure and dosage are now being made to determine the distributions of exposures in the general population and in specific target groups. These surveys measure exposure directly by biological sampling and/or personal monitoring of subjects air, food and water intake and dermal exposure or indirectly by questionnaire evaluation of the subjects diet and activities as a function of time and location. Samples of breath, blood, feces and urine that give biological measures of past exposures can be evaluated and interpreted for severity of effect by the percentage of the population exposed above a guideline level (e.g. exposure leading to 2% of the population exceeding 20 micrograms/dl lead in blood). Because the complete population cannot be sampled with 100% accuracy, errors will exist in the percent of population with a given exposure and the exposure for a given percent of the population. This paper discusses the accuracy considerations of the direct and indirect methods of exposure assessment and recommends a procedure for designing the surveys.

Data Collection↗

PubMedDate not supplied

Indoor and outdoor PM2.5 and CO in high- and low-density Guatemalan villages.

Continuous particles less than 2.5 microm in diameter (PM2.5) and carbon monoxide (CO) were monitored during breakfast, lunch, and dinner in three high-density and four low-density villages near Quetzaltenango, Guatemala to help assess the viability of this region for a proposed respiratory health and stove intervention study. Approximately 15 homes were visited during each mealtime in each of the seven villages; in all, 98 homes were visited, with a sampling duration of 2-3 min per home per meal. For each village, a line (transect) was drawn on a village map along existing roads from one end of the village to the other; homes and between-home outside locations along the transect were monitored. Although the predominant stove type was the open fire, several other stoves, in various levels of disrepair, were observed frequently. The highest indoor concentrations of PM2.5 were observed in homes using the open fire (avg. = 5.31 mg/m3; SD=4.75 mg/m3) or equivalent, although homes using the plancha--indigenous wood-burning stove with chimney--also had measurements > 13.8 mg/m3, PM2.5 limit of detection. The highest indoor concentrations of CO were also observed in homes using the open fire (avg. = 22.9 ppm; SD = 28.1 ppm), with a maximum measurement of > 250 ppm. For both PM2.5 and CO, levels measured in homes with plancha, lorena, or open fire were significantly higher than levels taken in the street or in homes using a gas stove. The Spearman correlation coefficient between PM2.5 and CO for all data combined was 0.81, and ranged from 0.30 for the lorena to 0.68 for the plancha in homes using wood-fueled stoves. Although indoor PM2.5 and CO levels were not significantly different between high- and low-density villages, street-level PM2.5 (p = 0.002) and CO (p= 0.002), were significantly higher in the high - density villages. These data provide a useful picture of the pollution levels coming from a range of cooking stoves in various levels ofdisrepair, as well as a representation of how outdoor particle mass and CO levels vary from high- versus low-density villages.

Air Pollution, Indoor↗