Grantee Research Project Results
2002 Progress Report: Health Effects of HAPs Among Inner Urban School Children
EPA Grant Number: R826789Title: Health Effects of HAPs Among Inner Urban School Children
Investigators: Greaves, Ian , Church, Timothy , Adgate, John L. , Ramachandran, Gurumurthy , Sexton, Ken
Institution: University of Minnesota
EPA Project Officer: Chung, Serena
Project Period: October 1, 1998 through September 30, 2001 (Extended to September 30, 2003)
Project Period Covered by this Report: October 1, 2001 through September 30, 2002
Project Amount: $633,044
RFA: Urban Air Toxics (1998) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air
Objective:
The objectives of this research project were to: (1) determine whether inner urban, poor, minority children attending grades 2-5 in a new "environmentally safe" school had lower rates of respiratory illness and better learning outcomes than similar children attending a nearby older school; (2) determine whether biomarkers of exposure and health effects differed among children in the two schools; (3) model the relationships between biomarkers and health outcomes; and (4) provide baseline data for a cohort who can be followed to see if childhood environmental exposures are associated with health problems in later life. Two null hypotheses were tested: the new school has no effect on health or learning outcomes among its students; and biomarkers of exposure are unrelated to health or learning outcomes.
Progress Summary:
This research project was approved by the University of Minnesota Research Subjects' Protection Program Institutional Review Board: Human Subjects' Committee, and was reviewed annually by that Committee.
The School Health Initiative: Environment, Learning and Disease (SHIELD) study evaluated young school children's environmental exposures, respiratory health, and learning abilities at a level of detail not previously attempted. Over a 2-year period, repeated environmental samples were obtained for air quality in schools, homes, and the general environment (samples included allergens and microbial elements); blood and urine were obtained on four occasions for biomarkers of exposure to tobacco smoke, heavy metals, volatile organic compounds (VOCs), and pesticides; annual questionnaires were administered for health and exposures; lung spirometry was performed annually; and standardized educational tests were administered. All of these procedures required the cooperation of parents, teachers, school administrators, the Minneapolis Public School District, community groups and, most importantly, the children.
School children in grades 2 through 5 were recruited from two inner urban schools in Minneapolis. One school (Whittier) was recently constructed and particular attention had been given to using building materials that were unlikely to present environmental health risks, minimizing the use of toxic building materials, avoiding carpets and other floor coverings that were likely to retain dust and other hazardous agents, and ensuring adequate ventilation and rates of air exchange. The second school (Lyndale) had been built in the 1970s, when building construction emphasized energy efficiency. It was thought that the older school likely presented greater environmental health risks to children.
A total of 153 out of 270 families (57 percent) from the two schools agreed to participate in the initial survey. We obtained data from 153 "index" children-those selected randomly from the school rolls to be participants-and an additional 48 siblings of the "index" children who wished to participate and also attended the same school. Almost all the children in this study received free school meals, an indicator of low family income. In the last few weeks of Year 1, 130 (85 percent) of the original 153 families had their children still enrolled at these schools. Those no longer enrolled were mostly children who frequently transferred among schools within the Minneapolis Public School District. At the start of Year 2 of the study, 136 (89 percent) of the original 153 families had children in these schools, and 107 of those families (that is, 70 percent of the original cohort) participated in the follow-up survey.
Data capture rates for blood and urine samples were high, averaging more than 90 percent for at least one sample, and about 85 percent for two samples of blood and urine in each year of the study. Participation in lung spirometry was similarly very high, with 90 percent of children completing the test in Year 1, and 96 percent in Year 2. Compliance with peak flow measurements was much lower because these measurements required students to collect and record their own data twice a day, on 3 days in 1 week, for 3 weeks of the year. In Year 1, about 77 percent of students completed 1 week of sampling, but only 32 percent completed all 3 weeks of sampling. Because of the time and frequency needed for this test, class activities were interrupted and compliance was affected by children’s absences due to field trips, illnesses, etc. The time needed for the peak flow measurements and the relatively low compliance rate in Year 1 prompted us not to repeat these measurements in Year 2.
The distribution of children by ethnicity/racial groups (see Table 1) illustrates the unusual diversity of ethnic and racial backgrounds of the children in this study, mostly related to the migration patterns over the last 20-30 years.
Ethnicity/Racial Group | Number |
Percentage of Total Group |
African Immigrants (Somali) | 52 |
25.9% |
African Americans | 46 |
22.9% |
Hispanics | 60 |
29.9% |
Other Racial Groups Asian (Cambodian) Asian (Laotian) Native American White Caucasian Other |
43 12 5 4 17 5 |
21.3% 6.0% 2.5% 2.0% 8.3% 2.5% |
Total | 201 |
100% |
* Data from Sexton, et al., 2000 and Sexton, et al., 2003. |
From the outset, participation rates were substantially less from homes where English was the first language (42 percent) than from non-English-speaking families (71 percent). This pattern of participation has been observed in other studies of inner urban populations. Among the English-speaking families, mostly African Americans, various recruitment and retention problems were more prominent: children transferred to other schools more frequently (19 percent versus 7 percent among non-English-speaking families); refusals to participate were higher (17 percent versus 8 percent); and failure to follow up after being contacted was more likely (15 percent versus 3 percent). In several cases, the children were willing to participate but parents could not be contacted to obtain their consent.
Despite these important practical issues, the results indicate that a school-based methodology makes it feasible and practical to conduct probability-based assessments of children’s environmental health in economically disadvantaged and ethnically diverse neighborhoods. The observations from this study suggest that further school-based investigations are likely to yield helpful information about children, particularly minority groups, and their environmental health problems. There is an ongoing need, however, to improve our understanding of the cultural, economic, psychological, and social determinants of study participation among these diverse groups. These and related issues are discussed more fully in papers devoted to this study's design, recruitment, retention, and compliance rates (Sexton, et al., 2000; Sexton, et al., 2003).
As discussed elsewhere (Needham, et al., 2000), assessing children's exposures is complex and challenging. Because we were interested in two primary health outcomes in relation to environmental exposures-respiratory disorders and learning ability-we prioritized our initial analyses and focused on exposures that were known to affect respiratory health or learning.
A major determinant of respiratory health in children is exposure to environmental tobacco smoke (ETS). Several approaches were used to assess children's exposures to ETS: questionnaire information was collected about the numbers of smokers in the home, the time spent around smokers, and whether the primary caregiver (usually a parent) smoked; time-activity logs were recorded by the children to determine the amount of time they were around smokers; and urine samples were obtained for tobacco-related biomarkers of exposure.
We measured cotinine + cotinine-glucuronide (total cotinine) as an indicator of exposure to ETS. Urine samples from 70 (33 percent) of 201 children had total cotinine levels greater than or equal to 5 ng/mL. Metabolites of the tobacco-specific lung carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) were used as an index of children’s exposure to carcinogens in ETS. The metabolites of NNK are 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) and its glucuronide (NNAL-Gluc). Of 74 samples for which there was sufficient urine to measure the metabolites of NNK, either NNAL or NNAL-Gluc was detected in 52 (96 percent) of the 54 samples with total cotinine greater than or equal to 5 ng/mL and in 10 (50 percent) of 20 samples with total cotinine less than 5 ng/mL. Levels of NNAL + NNAL-Gluc and total cotinine were significantly higher when exposure to ETS was reported in the questionnaire than when no exposure was reported. However, even when no exposure to ETS was reported, levels of NNAL, NNAL-Gluc, and NNAL + NNAL-Gluc were higher among those with total cotinine greater than or equal to 5 ng/mL than in children with total cotinine levels less than 5 ng/mL. Levels of NNAL, NNAL-Gluc, and total cotinine were not significantly different in samples collected twice from the same children at 3-month intervals.
Very limited data are available concerning carcinogen uptake by children exposed to ETS. Levels of the combined metabolites (NNAL + NNAL-Gluc) in this study were comparable to those observed in previous studies of nonsmoking adult women living with a spouse who smoked. There was a 93-fold range of NNAL + NNAL-Gluc values in the exposed children. The results demonstrated widespread and considerable uptake of the tobacco-specific lung carcinogen NNK in this group of elementary school-aged children, raising important questions about potential health risks. The data further indicate that objective biomarkers of carcinogen uptake are important in studies of childhood exposure to ETS and may be relevant to the development of tobacco-related cancer later in life. More detailed discussion of these findings can be found in Sexton, et al., 2000.
Additional consideration of ETS exposures revealed consistent differences by ethnicity and race based on three different estimates of ETS exposure: questionnaire responses; time-activity data; and total cotinine levels. Each exposure metric indicated that, on average, ETS exposures were highest for African American children, moderately high for those designated "Other," moderately low for Hispanic children, and lowest for Somali immigrant children.
The distribution of urinary total cotinine levels by ethnic/racial group illustrates these differences (see Table 2). Although there is some convergence of the groups at the high end of the distribution, values around the median (Q50) illustrate differences among the groups. These findings emphasize the importance of ethnic/racial characteristics when considering ETS exposures in children, and point to ways in which intervention strategies might be targeted to certain communities where smoking around children may present a significant health risk.
Table 2. Distribution of Urinary Cotinine Levels (ng/mL) for SHIELD "index" Children1 by Ethnicity/Racial Group: Distribution Range is From 5 Percent (Q5) to 95 Percent (Q95) of Values
Urinary Total Cotinine (ng/mL)2 |
||||||||
Ethnic/Racial Group | No. |
Q5 |
Q10 |
Q25 |
Q50 |
Q75 |
Q90 |
Q95 |
African Immigrants (Somali) | 33 |
0.23 |
0.23 |
0.23 |
0.23 |
3.0 |
6.1 |
30 |
African Americans | 31 |
0.23 |
0.23 |
0.5 |
9.0 |
28 |
34 |
38 |
Hispanics | 41 |
0.23 |
0.23 |
0.23 |
0.23 |
2.4 |
14 |
35 |
Other Racial Groups | 29 |
0.23 |
0.23 |
0.23 |
2.2 |
14 |
25 |
46 |
1 Includes primary child selected from a family but excludes any sibling who also participated. | ||||||||
2 Urinary Total Cotinine = cotinine + cotinine-N-glucuronide. | ||||||||
3 Samples below the detection limit of 0.4 ng/mL were assigned an arbitrary value of 0.2 ng/mL (i.e., half of the detection limit value). | ||||||||
These data and further details of total cotinine levels can be found in Sexton, et al., in press. |
Also of some interest was the predictive value for urinary cotinine that could be derived from questionnaire data and time-activity logs. Regression models were used to correlate urinary cotinine levels with responses to smoking-related questions on the initial questionnaire, with information from the time-activity logs, or with a combination of the two. Individually, questionnaire (Q) and time-activity (T-A) data predicted urinary total cotinine levels with reasonable reliability (adjusted r2 > 0.45), with the questionnaire doing a little better. A combination of Q + T-A data, however, performed better than either alone (adjusted r2 = 0.69). Because the questionnaire and time-activity information emphasized exposures to ETS in the home, the high correlation of total cotinine with Q + T-A data indicate that these children’s exposures to ETS are likely to be occurring mainly in the home.
Urinary cotinine is often considered the most direct, and therefore the best, indicator of ETS exposures. But collecting urine from children is challenging and laboratory analysis of large numbers of samples can be expensive. The present findings suggest that less expensive methods based on questionnaires or time-activity data can do almost as well in predicting children’s exposure to ETS.
Questionnaires, lung function tests, and allergy tests have contributed to understanding the nature and prevalence of respiratory illnesses among these children. Inner urban children have been shown to be at increased risk for asthma, other allergic conditions, and other respiratory illnesses including infections.
Samples of blood were available from 156 children to estimate total serum IgE levels and specific IgE titers to common allergens (see Table 3). Overall, the data indicated high rates of abnormal findings at each school, suggesting that atopy was common, but with somewhat different patterns in the specific IgE levels among the children at each school.
Overall, total and specific IgE levels were higher than one would expect in a population-based sample of elementary school children. Differences were apparent between the two schools. A higher fraction of children at Whittier had total IgE levels in excess of 100 IU/mL, but the difference between the two schools was not significant (P > 0.1). Elevated titers for specific IgE levels to cat and cockroach antigens were substantially greater among students at Whittier than at Lyndale (P < 0.001), while titers to dust mite (p1) (P < 0.001) and dust mite (f1) (0.05 < P < 0.1) were higher at Lyndale. Environmental measurements are ongoing to assess the levels of cat, house dust, and cockroach antigens in these children’s schools and homes.
Table 3. Allergy Testing Among Children Attending Two Inner Urban Schools in Minneapolis: Number (percent) Having Unusually High Blood Levels of Total IgE or Specific IgE Antibodies to Common Allergens*
Lyndale(N = 77) |
Whittier(N = 81) |
|
Total IgE (> 100 IU/mL) | 27 (35 percent) |
40 (49 percent) |
Ragweed (> 0.35 IU/mL) | 28 (36 percent) |
24 (30 percent) |
Dust mite (p1) (> 0.35 IU/mL) | 43 (56 percent) |
7 (9 percent) |
Dust mite (f1) (> 0.35 IU/mL) | 8 (10 percent) |
2 (2 percent) |
Cat (> 0.35 IU/mL) | 4 (5 percent) |
58 (72 percent) |
German cockroach (> 0.35 IU/mL) | 5 (6 percent) |
52 (64 percent) |
* Unpublished data from the laboratory of Dr. Malcom Blumenthal, University of Minnesota School of Medicine. |
Rates of asthma among these children are similar to studies of other children living in inner urban neighborhoods, but considerably higher than the national average provided by the National Health and Nutrition Examination Survey (NHANES) showing that 5.5 percent of children experienced asthma in the last 12 months. Depending on how one chooses to define asthma, the rate in this population was 12.0 percent for those who had been diagnosed by a physician as having asthma, 9.0 percent for those who had experienced at least one episode of asthma in the last year, and 7.0 percent for those who were currently taking medications for their asthma. These numbers likely underestimate the true rates of asthma in this population. One reason for this is the relative lack of access to health care for poor inner urban families.
Objective measurements of lung function are another way to assess the presence of asthma. Ventilatory function tests were obtained from children in each school during late winter and spring of 2000, and again in late winter and spring of 2001. These tests were performed by National Institute for Occupational Safety and Health (NIOSH)-certified technicians using two Survey Rolling-Seal Spirometers (Warren E. Collins, Massachusetts) that were calibrated before and after each testing session. The spirometers were connected to computers, which recorded all data digitally and stored it for later analysis. Lung function was evaluated for each child using race-specific predicted values. The data of Hsu, et al. (1979), were used to obtain predicted values for white Caucasian, Mexican American (Hispanic), and African American children. There are no published prediction equations for immigrant Africans so we used the same prediction equations as African Americans. Native American and Asian children were assigned the prediction equations of white Caucasians.
Data obtained in 2000 (see Table 4) showed that several lung function parameters were less than expected for each of the four racial groups, particularly the group means for the forced expiratory volume in 1-second (FEV1) and the maximum mid-expiratory flow (MMEF). In contrast, measurements of forced vital capacity (FVC) were similar to the race-specific predicted values. This pattern of lung function findings, with decreased FEV1 and MMEF and a well preserved FVC, is characteristic of an "obstructive" lung disorder such as asthma. This suggested that a substantial number of children could have asthma that was unrecognized.
The follow-up data of 2001 did not support that conclusion, however (see Table 4). We were able to remeasure lung function in 75 percent of the original children. The decline in participation was most marked among African American children. When retested, the average lung function values for each ethnic/racial group were very close to the respective predicted values. There are several possible explanations for these findings. For example, it is known that indirect standardization of lung function measurements based on data from other populations may lead to errors and introduce bias, particularly when race-specific data are lacking. These potential problems are being addressed by exploring different statistical analyses that do not rely on reference data from other populations.
Measurements of peak flow were obtained from children in grades 3 and 4 during Year 1. These data are being analyzed further in relation to diurnal patterns of lung function change within a day and across weeks and seasons. The associations of repeated peak flow measurements to asthma, atopy, respiratory symptoms, spirometry, and various environmental exposures are being explored.
2000 | 2001 | ||||||||||
N |
Mean (SD) |
Q10 |
Q50 |
Q90 |
N |
Mean (SD) |
Q10 |
Q50 |
Q90 |
||
African American | |||||||||||
FEV1 (L) | Actual | 48 |
1.67 (0.35) |
1.27 |
1.66 |
2.19 |
25 |
1.94 (0.42) |
1.52 |
1.90 |
2.61 |
Predicted | 1.76 (0.36) |
1.39 |
1.70 |
2.15 |
1.78 (0.30) |
1.46 |
1.70 |
2.27 |
|||
FVC (L) | Actual | 48 |
1.93 (0.47) |
1.39 |
1.83 |
2.50 |
25 |
2.28 (0.55) |
1.63 |
2.22 |
3.02 |
Predicted | 1.83 (0.37) |
1.42 |
1.80 |
2.29 |
2.06 (0.37) |
1.69 |
1.97 |
2.57 |
|||
MMEF (L/s) | Actual | 48 |
2.01 (0.50) |
1.28 |
2.05 |
2.70 |
25 |
2.19 (0.53) |
1.43 |
2.21 |
2.92 |
Predicted | 2.58 (0.44) |
2.10 |
2.53 |
3.08 |
2.43 (0.30) |
2.12 |
2.36 |
2.89 |
|||
PEF (L/s) | Actual | 48 |
3.69 (1.02) |
2.53 |
3.59 |
4.59 |
25 |
4.20 (0.94) |
2.88 |
4.47 |
5.17 |
Predicted | 4.95 (0.83) |
4.03 |
5.63 |
6.04 |
4.63 (0.74) |
3.72 |
4.51 |
5.78 |
|||
African Immigrant (Somali) | |||||||||||
FEV1 (L) | Actual | 53 |
1.81 (0.45) |
1.22 |
1.79 |
2.34 |
42 |
2.11 (0.45) |
1.54 |
2.11 |
2.77 |
Predicted | 2.02 (0.38) |
1.51 |
2.00 |
2.53 |
1.97 (0.31) |
1.57 |
1.98 |
2.31 |
|||
FVC (L) | Actual | 53 |
2.01 (0.52) |
1.41 |
1.98 |
2.62 |
42 |
2.28 (0.49) |
1.67 |
2.31 |
2.93 |
Predicted | 2.09 (0.39) |
1.60 |
2.12 |
2.69 |
2.29 (0.37) |
1.78 |
2.29 |
2.69 |
|||
MMEF (L/s) | Actual | 53 |
2.52 (0.81) |
1.54 |
2.38 |
3.76 |
42 |
3.17 (0.93) |
2.07 |
3.00 |
4.43 |
Predicted | 2.89 (0.45) |
2.24 |
2.90 |
3.48 |
2.68 (0.37) |
2.21 |
2.66 |
3.12 |
|||
PEF (L/s) | Actual | 53 |
3.90 (1.04) |
2.53 |
3.73 |
5.41 |
42 |
4.86 (1.23) |
3.53 |
4.56 |
7.00 |
Predicted | 5.55 (0.84) |
4.39 |
5.63 |
6.87 |
5.23 (0.69) |
4.25 |
5.25 |
6.08 |
|||
Hispanic | |||||||||||
FEV1 (L) | Actual | 58 |
1.75 (0.37) |
1.29 |
1.72 |
2.19 |
46 |
2.10 (0.49) |
1.52 |
2.12 |
2.71 |
Predicted | 1.95 (0.39) |
1.54 |
1.92 |
2.53 |
2.02 (0.32) |
1.61 |
2.06 |
2.46 |
|||
FVC (L) | Actual | 58 |
2.07 (0.48) |
1.50 |
2.07 |
2.64 |
46 |
2.40 (0.54) |
1.73 |
2.45 |
2.97 |
Predicted | 2.03 (0.39) |
1.56 |
2.04 |
2.69 |
2.32 (0.38) |
1.82 |
2.37 |
2.81 |
|||
MMEF (L/s) | Actual | 58 |
2.00 (0.71) |
1.05 |
1.99 |
2.97 |
46 |
2.58 (0.78) |
1.61 |
2.41 |
3.65 |
Predicted | 2.45 (0.42) |
1.98 |
2.44 |
3.08 |
2.37 (0.30) |
1.99 |
2.38 |
2.70 |
|||
PEF (L/s) | Actual | 58 |
3.61 (0.86) |
2.47 |
3.73 |
4.76 |
46 |
4.29 (0.84) |
3.18 |
4.35 |
5.23 |
Predicted | 4.70 (0.80) |
3.79 |
4.74 |
5.99 |
4.45 (0.71) |
3.44 |
4.46 |
5.47 |
|||
"Other" | |||||||||||
FEV1 (L) | Actual | 45 |
1.70 (0.37) |
1.20 |
1.72 |
2.15 |
39 |
1.88 (0.37) |
1.38 |
1.95 |
2.34 |
Predicted | 1.90 (0.36) |
1.46 |
1.90 |
2.36 |
1.93 (0.30) |
1.54 |
1.98 |
2.31 |
|||
FVC (L) | Actual | 45 |
1.92 (0.48) |
1.31 |
1.93 |
2.49 |
39 |
2.12 (0.47) |
1.57 |
2.16 |
2.60 |
Predicted | 1.97 (0.38) |
1.47 |
1.98 |
2.38 |
2.23 (0.36) |
1.78 |
2.27 |
2.70 |
|||
MMEF (L/s) | Actual | 45 |
2.16 (0.51) |
1.55 |
2.19 |
2.78 |
39 |
2.37 (0.55) |
1.62 |
2.42 |
2.98 |
Predicted | 2.42 (0.40) |
1.98 |
2.41 |
2.90 |
2.31 (0.26) |
2.04 |
2.25 |
2.66 |
|||
PEF (L/s) | Actual | 45 |
3.59 (0.75) |
2.65 |
3.47 |
4.53 |
39 |
4.08 (0.80) |
3.06 |
3.94 |
5.23 |
Predicted | 4.63 (0.76) |
3.79 |
4.62 |
5.63 |
4.35 (0.67) |
3.66 |
4.19 |
5.19 |
|||
Abbreviations: FEV1 = forced expiratory volume in 1-second (Liters) MMEF = Maximum mid-expiratory flow (Liters/sec) FVC = forced vital capacity (Liters) PEF = Peak expiratory flow (Liters/sec) |
Other outcome measurements to be considered relate to the performance of these children in school. Performance scores of these children on nationally standardized education tests have been obtained from the Minneapolis Public School District. These data will be analyzed in relation to a variety of environmental exposure measurements, including VOCs, pesticides, metals, and measures of indoor air quality that have been associated with nonspecific symptoms, including difficulty concentrating and memory loss.
Companion studies to the one reported here have measured biomarkers of exposure in the blood or urine to VOCs, pesticides, organochlorine compounds, and heavy metals in these children during the same period as the measurements of health outcomes. In addition, we have measured ambient exposures to airborne particles (PM2.5) and VOCs, and indoor air samples (both in the schools and homes) for airborne particles (PM2.5), VOCs, molds, and common allergens. Sample analysis is complete, and data analysis for publication is proceeding.
References:
Hsu KH, et al. Ventilatory functions of normal children and young adults¾Mexican-American, white, and black. I. Spirometry. Journal of Pediatrics 1979;95:14-23.
Future Activities:
In the final year of the extended grant, we will complete several manuscripts and prepare the final report for the project.
Journal Articles on this Report : 6 Displayed | Download in RIS Format
Other project views: | All 14 publications | 14 publications in selected types | All 14 journal articles |
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Type | Citation | ||
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Hecht SS, Ye M, Carmella SG, Fredrickson A, Adgate JL, Greaves IA, Church TR, Ryan AD, Mongin SJ, Sexton K. Metabolites of a tobacco-specific lung carcinogen in the urine of elementary school-aged children. Cancer Epidemiology, Biomarkers & Prevention 2001;10(11):1109-1116. |
R826789 (2000) R826789 (2001) R826789 (2002) R826789 (Final) R825813 (2001) |
Exit Exit |
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Needham LL, Sexton K. Assessing children's exposure to hazardous environmental chemicals: an overview of selected research challenges and complexities. Journal of Exposure Analysis and Environmental Epidemiology 2000;10(6 Pt 2):611-629. |
R826789 (2002) R826789 (Final) R825813 (2001) |
Exit Exit |
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Sexton K, Greaves IA, Church TR, Adgate JL, Ramachandran G, Tweedie RL, Fredrickson A, Geisser M, Sikorski M, Fischer G, Jones D, Ellringer P. A school-based strategy to assess children's environmental exposures and related health effects in economically disadvantaged urban neighborhoods. Journal of Exposure Analysis and Environmental Epidemiology 2000;10(6 Pt 2):682-694. |
R826789 (2000) R826789 (2001) R826789 (2002) R826789 (Final) R825813 (2000) R825813 (2001) |
Exit Exit |
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Sexton K, Adgate JL, Church TR, Greaves IA, Ramachandran G, Fredrickson AL, Geisser MS, Ryan AD. Recruitment, retention, and compliance results from a probability study of children's environmental health in economically disadvantaged neighborhoods. Environmental Health Perspectives 2003;111(5):731-736. |
R826789 (2002) R826789 (Final) |
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Sexton K, Waller LA, McMaster RB, Maldonado G, Adgate JL. The importance of spatial effects for environmental health policy and research. Human and Ecological Risk Assessment 2004;8(1):109-125. |
R826789 (2002) R826789 (Final) R825241 (Final) |
Exit |
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Sexton K, Adgate JL, Church TR, Hecht SS, Ramachandran G, Greaves IA, Fredrickson AL, Ryan AD, Carmella SG, Geisser MS. Children's exposure to environmental tobacco smoke:using diverse exposure metrics to document ethnic/racial differences. Environmental Health Perspectives 2004;112(3):392-397. |
R826789 (2002) R826789 (Final) R832734 (Final) |
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Supplemental Keywords:
school children, inner urban, low-income, indoor air pollution, airborne particles, heavy metals, volatile organic compounds, VOCs, tobacco smoke, pesticides, allergies, asthma, learning, questionnaires, blood tests, urine tests, lung function, minority groups, African American, Somali, Hispanic, Asian, Cambodian, Laotian, Native American., RFA, Health, Scientific Discipline, Air, Toxics, Geographic Area, air toxics, Environmental Chemistry, Health Risk Assessment, Epidemiology, State, VOCs, Risk Assessments, Susceptibility/Sensitive Population/Genetic Susceptibility, Biochemistry, Children's Health, genetic susceptability, indoor air, Ecology and Ecosystems, asthma, urban air, pesticide exposure, monitoring, ambient air quality, atmospheric, risk assessment, sensitive populations, urban air toxics, building related illness, emission inventory, urban monitoring sites, Minnesota, MN, air pollutants, biological sensitivities, infants, inner urban school children, lung, buildings, health risks, urban school children, airway disease, measuring childhood exposure, respiratory problems, ambient air, HAPS, hazardous air pollutants, pesticides, susceptible populations, exposure, Human Health Risk Assessment, air pollution, children, emissions, pulmonary toxicity, urban air pollutants, ethnic groups, assessment of exposure, childhood respiratory disease, children's vulnerablity, inhalation, human exposure, allergic, toxicity, pulmonary, sick building syndrome, urine and blood samples, environmental toxicant, harmful environmental agents, urban air pollution, inhaled, schools, biological markers, indoor air quality, human health, sensitive population, allergen, allergies, disease, Minneapolis-St.Paul Metropolitan area, respiratory, VOC sensitivity, air quality, autoimmunityProgress 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.