Family-based association studies

We review case-control designs for studying gene associations in which relatives of case patients are used as control subjects. These designs have the advantage that they avoid the problem of population stratification that can lead to spurious associations with noncausal genes. We focus on designs that use sibling, cousin, or pseudosibling controls, the latter formed as the set of genotypes not transmitted to the case from his or her parents. We describe a common conditional likelihood framework for use in analyzing data from any of these designs and review what is known about the validity of the various design and analysis combinations for estimating the genetic relative risk. We also present comparisons of efficiency for each of the family-based designs relative to the standard population-control design in which unrelated controls are selected from the source population of cases. Because of overmatching on genotype, the use of sibling controls leads to estimates of genetic relative risk that are approximately half as efficient as those obtained with the use of population controls, while relative efficiency for cousin controls is approximately 90%. However, we find that, for a rare gene, the sibling-control design can lead to improved efficiency for estimating a G x E interaction effect. We also review some restricted designs that can substantially improve efficiency, e.g., restriction of the sample to case-sibling pairs with an affected parent. We conclude that family-based case-control studies are an attractive alternative to population-based case-control designs using unrelated control subjects.

Cohort studies for characterizing measured genes

We describe the advantages of using established cohort studies that have collected blood samples to investigate the role of genes in the etiology of cancer. These studies include the cost-efficiency and reliability of nested case-control substudies from the cohort for exploration of gene-disease associations and gene-environment interactions as well as gene penetrance. Also, the cohort may serve as a well-defined "mini-population" from which to study population stratification and molecular markers of ethnicity. We conclude that cohort studies can play a significant role in assessing the role of genetic markers for common tumors or multiple cancer sites.

Study-design issues in the development of the University of Southern California Consortium's Colorectal Cancer Family Registry

The University of Southern California Consortium is a participating center in the National Cancer Institute's Collaborative Family Registry for Colorectal Cancer Studies (CFRCCS). Because data collection takes time, money, and effort, all of which are in short supply, we first defined our research objectives and then attempted to design our registry to enable us to address these objectives in an efficient manner. We decided on a family-based design, and our objectives are to characterize cloned genes that are generally accepted causes of colorectal cancer, to assess putative candidate genes, to map new genes, and to conduct prevention trials in high-risk subjects. For the gene characterization objectives, our primary aim is to estimate gene frequency and penetrance, with a secondary aim to investigate factors that may affect penetrance (allele-specific effects plus gene-gene and gene-environment interactions). We describe a multiple-stage design to select families into the registry. After a family is selected into the registry, we collect questionnaire data and blood samples on selected subjects only, and we tailor data collection decisions to each family (given who is affected and who is available) to optimize power per unit effort and cost. We also discuss practical decisions faced by our registry, including 1) defining a reference period for use in questionnaires; 2) deciding whether or not to establish cell lines and, if so, on whom; and 3) determining which cases should be tested for microsatellite instability. Finally, we address the appropriate use of data derived from high-risk clinics, within more broadly defined, population-based research.

Design of gene characterization studies: an overview

This collection of papers from the Gene Characterization Panel addresses design issues in studies aimed at assessing the population characteristics of cloned genes, such as their allele frequencies, penetrance, variation in these parameters across subpopulations, and gene-environment and gene-gene interactions. This paper provides an overview of the various designs that have been suggested, including cohort and case-control designs using independent and related individuals as well as optimal multistage sampling and hybrid designs. Various statistical (bias and efficiency) and practical considerations are suggested for evaluation of the alternative designs, with the aim of posing the question, "What is the optimal design for a particular situation"? The answer to this question clearly depends on such contextual issues as nature of the outcome variable, the gene frequency and genetic relative risk, and the importance of gene-environment and gene-gene interactions. Further methodologic work might be usefully directed toward assessment of the seriousness of the population stratification problem in general as well as methods of dealing with it, the utility of registries of high-risk families, and the merits of various hybrid designs for gene discovery and gene characterization.

Testing linkage disequilibrium in sibships

We describe the use of multivariate regression for testing allelic association in the presence of linkage, using marker genotype data from sibships. The test is valid, provided that the correct mean structure is modeled but does not require the correlation structure within families to be specified. The test can be implemented using standard statistical software such as the SAS programming language. In a simulation study, we evaluated this new test in comparison with one from a standard, matched-case-control analysis. First, we noted that the genetic effect needed to be quite extreme before residual familial correlation due to linkage led to false inference using the standard, matched-pair analysis. Second, we showed that under examples of extreme residual familial correlation, the new test had the correct test size. Third, we found that the test was more powerful than the sibship disequilibrium test of Horvath and Laird. Finally, we concluded that although the standard analysis may lead to correct inference for practical purposes, the new test is valid, even under extreme residual familial correlation and with no cost in power at the causal locus.

A Bayesian approach to multipoint mapping in nuclear families

We describe the application of a Markov Chain Monte Carlo approach for multipoint mapping of a quantitative trait locus to the Nuclear Families simulated data. The method involves repeated sampling of genotype vectors for each nuclear family from their conditional distributions, given phenotypes, markers, and model parameters, using peeling and gene dropping, followed by random sampling of each model parameter given genotypes and the other parameters. Reversible jump methods are used to sample the number of trait loci.

Analysis of gene-smoking interaction in lung cancer

The Louisiana Lung Cancer Dataset, consisting of 337 extended pedigrees, is analyzed to determine whether a major Mendelian gene interacts with cumulative tobacco smoking (pack-years). The proportional hazards model is utilized, as it is a natural framework for estimating relative risks while adjusting for variability in age of disease onset. Segregation analyses show evidence that a Mendelian gene is segregating in these families, with the most parsimonious model, including sex, pack-years, pack-years squared, and a dominant major gene. The estimated frequency of the high-risk allele is 2% and carriers are estimated to have relative risk of 17.3 for developing lung cancer, compared to noncarriers. The addition of a gene x pack-years interaction does not significantly improve the fit of the model, indicating that on a multiplicative scale, these two factors independently influence lung cancer risk. Smoking history is missing for 23% of the study subjects and degree of "missingness" depends on disease status, age, and birth-year. To account for the nonrandomness of the missing data, a Markov chain Monte Carlo method for covariate imputation is proposed and implemented. Results from this analysis also support a nonsignificant gene-smoking interaction and an allele frequency of 2%, but a lower genetic relative risk (9.0) compared to the "complete case" analysis.

Bias and efficiency in family-based gene-characterization studies: conditional, prospective, retrospective, and joint likelihoods

We revisit the usual conditional likelihood for stratum-matched case-control studies and consider three alternatives that may be more appropriate for family-based gene-characterization studies: First, the prospective likelihood, that is, Pr(D/G,A second, the retrospective likelihood, Pr(G/D); and third, the ascertainment-corrected joint likelihood, Pr(D,G/A). These likelihoods provide unbiased estimators of genetic relative risk parameters, as well as population allele frequencies and baseline risks. The parameter estimates based on the retrospective likelihood remain unbiased even when the ascertainment scheme cannot be modeled, as long as ascertainment only depends on families' phenotypes. Despite the need to estimate additional parameters, the prospective, retrospective, and joint likelihoods can lead to considerable gains in efficiency, relative to the conditional likelihood, when estimating genetic relative risk. This is true if baseline risks and allele frequencies can be assumed to be homogeneous. In the presence of heterogeneity, however, the parameter estimates assuming homogeneity can be seriously biased. We discuss the extent of this problem and present a mixed models approach for providing consistent parameter estimates when baseline risks and allele frequencies are heterogeneous. The efficiency gains of the mixed-model prospective, retrospective, and joint likelihoods relative to the efficiency of conditional likelihood are small in the situations presented here.

A generalized estimating equations approach to linkage analysis in sibships in relation to multiple markers and exposure factors

We describe a multiple regression approach to nonparametric linkage analysis in sibships incorporating multiple genetic loci, environmental covariates, and interactions. The covariance in trait residuals between sib pairs is treated as the dependent variable, regressed upon identical-by-descent sharing probabilities and interaction effects, using generalized estimating equations to allow for the correlations among multiple sib pairs within a sibship. Individual covariates can also be introduced in the model for the trait means. An application to the GAW11 simulated data revealed linkage with each of the four simulated loci, as well as gene x environment interactions of E1 with loci C and D and gene x gene interactions among the cluster of loci A, B, and D.

A joint test of linkage and gene x environment interaction, with affected sib pairs

In the presence of gene x environment (G x E) interaction, the expected proportion of alleles shared identical by descent at a linked marker locus by a pair of affected sibs depends on the exposure profile of the two sibs, i.e., whether both are exposed to E, only one is exposed, or neither are exposed. In this paper, we propose an extension of the commonly used mean test of linkage to test for differential identical-by-descent (IBD) sharing across sib-exposure profiles. The method can be viewed as a test for linkage in the presence of G x E interaction, or as a test for G x E interaction in the presence of linkage. Applied to the simulated GAW11 data, our method successfully localized disease locus C and its interactive relationship with environmental factor E1. At the 5% significance level, use of our method led to increased power to detect linkage (56%) to this disease locus compared to use of the standard mean test (32%); at the 0.001 significance level, the corresponding power estimates were 20% and 4%, respectively. For a gene that interacts with an environmental factor, we conclude that use of the environmental factor in linkage analysis can improve detection rates while also providing information about underlying mechanisms.

Association tests using unaffected-sibling versus pseudo-sibling controls

We used family-matched case-control data to screen the genome for markers associated with disease in the simulated data set. Two different types of controls were considered: (1) unaffected siblings and (2) 'pseudo siblings,' a comparison sample created using the parental alleles. The scans were conducted on the first replicate of each study population. Overall, the two methods identified 14 marker loci associated with disease at the 0.001 significance level. Marker D1G24 (locus D) was the only true disease locus found by both approaches. No associations were found at any of the markers flanking the unobserved disease susceptibility loci (A, B, or C). We subsequently pooled the 25 replicates from a single population. This large sample still did not yield any associations at the flanking markers. We tested for association at locus D using a pseudo-sib approach restricted to alleles shared identical by descent between affected sib pairs. The power was 44% (11/25 replicates) at a significance level of 0.001.

Ascertainment bias in rate ratio estimation from case-sibling control studies of variable age-at-onset diseases

Motivated by a Finnish case-control study of early onset diabetes in which diabetic children are matched to sibling controls, we investigate ascertainment bias of the usual rate ratio estimator from case-control data under simplex complete ascertainment of families during a fixed interval of time. Analytic results indicate that the assumptions necessary for valid estimation are that the disease is rare and the factors under study are exchangeable--essentially that the covariate distribution does not depend on calendar time or birth order. Further, we found that the rare disease assumption could be dropped by restricting to cases that were diagnosed during the enrollment period of the study or including all cases but eliminating the proband as a control for non-enrollment-period cases. An important consequence of this work is that standard family-based case-control studies are subject to ascertainment bias if exchangeability of the covariates under investigation does not hold.

Amplification of padlock probes for DNA diagnostics by cascade rolling circle amplification or the polymerase chain reaction

CONTEXT

Padlock probes are highly specific reagents for DNA diagnostics that can discriminate gene sequences with single base mutations. When the 3' and 5' terminal regions of the oligonucleotide probes are juxtaposed on a target DNA sequence, they can be circularized by enzymatic ligation and become topologically locked to the target. However, to be useful in solution-based diagnostics, the sensitivity of padlock probes must be markedly enhanced.

OBJECTIVE

To describe two methods for geometric amplification of circularized padlock probes.

DESIGN

Cascade rolling circle amplification is an isothermal system that uses generic primers and a DNA polymerase with strong strand displacement activity to amplify circularized probes by a mechanism combining rolling circle replication and strand displacement synthesis. One of the primers was designed as an energy transfer-labeled primer, which generates a fluorescence signal only when incorporated into the amplified product, enabling a direct means of detection.

RESULTS

Using pUC19 as a model target to circularize an 89-base probe, a 10 billion-fold amplification was achieved with Bst DNA polymerase (large fragment) within 1 hour starting with as few as 10 probe molecules. The polymerase chain reaction was also used to amplify ligated padlock probes in a rare target detection system. In mixing experiments containing both normal and mutant p53 or c-Ki-ras2 gene target sequences, mutant targets were easily detected in the presence of a 500-fold excess of normal target copies.

CONCLUSION

These results indicate that padlock probes can be amplified to the high levels required for solution-based DNA diagnostics.

Amplification of Padlock Probes for DNA Diagnostics by Cascade Rolling Circle Amplification or the Polymerase Chain Reaction

Context.—Padlock probes are highly specific reagents for DNA diagnostics that can discriminate gene sequences with single base mutations. When the 3′ and 5′ terminal regions of the oligonucleotide probes are juxtaposed on a target DNA sequence, they can be circularized by enzymatic ligation and become topologically locked to the target. However, to be useful in solution-based diagnostics, the sensitivity of padlock probes must be markedly enhanced.

Objective.—To describe two methods for geometric amplification of circularized padlock probes.

Design.—Cascade rolling circle amplification is an isothermal system that uses generic primers and a DNA polymerase with strong strand displacement activity to amplify circularized probes by a mechanism combining rolling circle replication and strand displacement synthesis. One of the primers was designed as an energy transfer–labeled primer, which generates a fluorescence signal only when incorporated into the amplified product, enabling a direct means of detection.

Results.—Using pUC19 as a model target to circularize an 89-base probe, a 10 billion–fold amplification was achieved with Bst DNA polymerase (large fragment) within 1 hour starting with as few as 10 probe molecules. The polymerase chain reaction was also used to amplify ligated padlock probes in a rare target detection system. In mixing experiments containing both normal and mutant p53 or c-Ki-ras2 gene target sequences, mutant targets were easily detected in the presence of a 500-fold excess of normal target copies.

Conclusion.—These results indicate that padlock probes can be amplified to the high levels required for solution-based DNA diagnostics.

Residential magnetic fields predicted from wiring configurations: II. Relationships To childhood leukemia

Case-control data on childhood leukemia in Los Angeles County were reanalyzed with residential magnetic fields predicted from the wiring configurations of nearby transmission and distribution lines. As described in a companion paper, the 24-h means of the magnetic field's magnitude in subjects' homes were predicted by a physically based regression model that had been fitted to 24-h measurements and wiring data. In addition, magnetic field exposures were adjusted for the most likely form of exposure assessment errors: classic errors for the 24-h measurements and Berkson errors for the predictions from wire configurations. Although the measured fields had no association with childhood leukemia (P for trend=.88), the risks were significant for predicted magnetic fields above 1.25 mG (odds ratio=2.00, 95% confidence interval=1.03-3.89), and a significant dose-response was seen (P for trend=.02). When exposures were determined by a combination of predictions and measurements that corrects for errors, the odds ratio (odd ratio=2.19, 95% confidence interval=1.12-4.31) and the trend (p =.007) showed somewhat greater significance. These findings support the hypothesis that magnetic fields from electrical lines are causally related to childhood leukemia but that this association has been inconsistent among epidemiologic studies due to different types of exposure assessment error. In these data, the leukemia risks from a child's residential magnetic field exposure appears to be better assessed by wire configurations than by 24-h area measurements. However, the predicted fields only partially account for the effect of the Wertheimer-Leeper wire code in a multivariate analysis and do not completely explain why these wire codes have been so often associated with childhood leukemia. The most plausible explanation for our findings is that the causal factor is another magnetic field exposure metric correlated to both wire code and the field's time-averaged magnitude.

Residential magnetic fields predicted from wiring configurations: I. Exposure model

A physically based model for residential magnetic fields from electric transmission and distribution wiring was developed to reanalyze the Los Angeles study of childhood leukemia by London et al. For this exposure model, magnetic field measurements were fitted to a function of wire configuration attributes that was derived from a multipole expansion of the Law of Biot and Savart. The model parameters were determined by nonlinear regression techniques, using wiring data, distances, and the geometric mean of the ELF magnetic field magnitude from 24-h bedroom measurements taken at 288 homes during the epidemiologic study. The best fit to the measurement data was obtained with separate models for the two major utilities serving Los Angeles County. This model's predictions produced a correlation of 0.40 with the measured fields, an improvement on the 0.27 correlation obtained with the Wertheimer-Leeper (WL) wire code. For the leukemia risk analysis in a companion paper, the regression model predicts exposures to the 24-h geometric mean of the ELF magnetic fields in Los Angeles homes where only wiring data and distances have been obtained. Since these input parameters for the exposure model usually do not change for many years, the predicted magnetic fields will be stable over long time periods, just like the WL code. If the geometric mean is not the exposure metric associated with cancer, this regression technique could be used to estimate long-term exposures to temporal variability metrics and other characteristics of the ELF magnetic field which may be cancer risk factors.

Fluid dynamic characterization of operating conditions for continuous flow blood pumps

As continuous flow pumps become more prominent as long-term ventricular assist devices, the wide range of conditions under which they must be operated has become evident. Designed to operate at a single, best-efficiency, operating point, continuous flow pumps are required to perform at off-design conditions quite frequently. The present study investigated the internal fluid dynamics within two representative rotary fluid pumps to characterize the quality of the flow field over a full range of operating conditions. A Nimbus/UoP axial flow blood pump and a small centrifugal pump were used as the study models. Full field visualization of flow features in the two pumps was conducted using a laser based fluorescent particle imaging technique. Experiments were performed under steady flow conditions. Flow patterns at inlet and outlet sections were visualized over a series of operating points. Flow features specific to each pump design were observed to exist under all operating conditions. At off-design conditions, an annular region of reverse flow was commonly observed within the inlet of the axial pump, while a small annulus of backflow in the inlet duct and a strong disturbed flow at the outlet tongue were observed for the centrifugal pump. These observations were correlated to a critical nondimensional flow coefficient. The creation of a "map" of flow behavior provides an additional, important criterion for determining favorable operating speed for rotary blood pumps. Many unfavorable flow features may be avoided by maintaining the flow coefficient above a characteristic critical coefficient for a particular pump, whereas the intrinsic deleterious flow features can only be minimized by design improvement. Broadening the operating range by raising the band between the critical flow coefficient and the designed flow coefficient, is also a worthy goal for design improvement.

Correcting for exposure measurement error in a reanalysis of lung cancer mortality for the Colorado Plateau Uranium Miners cohort

The exposure estimates used to date for the analysis of lung cancer mortality in the Colorado Plateau Uranium Miners cohort were developed from radon progeny measurements taken in mines beginning in 1951. Since uranium miners were often exposed over long periods of time and since mines were not continuously monitored, much extrapolation and/or interpolation of measured dose-rates was needed in order to develop estimates of exposure for each of the miners in the cohort. We have recently re-examined the interpolation scheme used to create the histories in the light of the fit of a statistical model for the radon progeny measurements taken in mines within the Plateau, and we have computed revised exposure estimates for the large majority of miners in the cohort. This report describes the use of these new model-based revised exposure estimates in the analysis of lung cancer mortality, using follow-up data current through 1990. Specific issues addressed here are (1) the strength of the association between exposure and risk of lung cancer mortality; (2) effects of attained age and time since exposure upon risk of lung cancer mortality; and (3) exposure-rate effects upon risk. Results using the revised exposure estimates are compared to those obtained fitting the same models using the original Public Health Service (PHS) exposure estimates. We found evidence that the new exposure histories provide a better fit to the lung cancer mortality data than do the histories based upon the original PHS dose-rate estimates. In general, the new results show a stronger overall relationship (larger slope estimate) between lung cancer mortality and exposure per unit exposure compared to those obtained with the original estimates, while displaying similar age at exposure and time since exposure effects. In the reanalysis the impact of low dose-rate exposure is found to be relatively unchanged before and after exposure error correction, while the estimate of the effect of high dose-rate exposure is considerably increased. Even after applying our measurement error corrections, evidence of inverse dose-rate effects is found, since the estimate of the impact of high dose-rate exposure is still below that of the low dose-rates. The magnitude and statistical significance, however, of the dose-rate effect estimates are diminished when fit using the revised exposure estimates.

Air pollution and bronchitic symptoms in Southern California children with asthma

The association of air pollution with the prevalence of chronic lower respiratory tract symptoms among children with a history of asthma or related symptoms was examined in a cross-sectional study. Parents of a total of 3,676 fourth, seventh, and tenth graders from classrooms in 12 communities in Southern California completed questionnaires that characterized the children's histories of respiratory illness and associated risk factors. The prevalences of bronchitis, chronic phlegm, and chronic cough were investigated among children with a history of asthma, wheeze without diagnosed asthma, and neither wheeze nor asthma. Average ambient annual exposure to ozone, particulate matter (PM(10) and PM(2.5); [less than/equal to] 10 microm and < 2.5 microm in aerodynamic diameter, respectively), acid vapor, and nitrogen dioxide (NO(2)) was estimated from monitoring stations in each community. Positive associations between air pollution and bronchitis and phlegm were observed only among children with asthma. As PM(10) increased across communities, there was a corresponding increase in the risk per interquartile range of bronchitis [odds ratio (OR) 1.4/19 microg/m(3); 95% confidence interval (CI), 1.1-1.8). Increased prevalence of phlegm was significantly associated with increasing exposure to all ambient pollutants except ozone. The strongest association was for NO(2), based on relative risk per interquartile range in the 12 communities (OR 2.7/24 ppb; CI, 1.4-5.3). The results suggest that children with a prior diagnosis of asthma are more likely to develop persistent lower respiratory tract symptoms when exposed to air pollution in Southern California.

Chronic animal health assessment during axial ventricular assistance: importance of hemorheologic parameters

Chronic testing of the Nimbus/UOP Axial Flow Pump was performed on 22 calves for periods of implantation ranging from 27 to 226 days (average, 74 days). The following parameters were measured: plasma free hemoglobin, blood and plasma viscosity, erythrocyte deformability and mechanical fragility, oxygen delivery index (ODI), blood cell counts, hematocrit, hemoglobin, blood urea nitrogen, creatinine, bilirubin, total protein, fibrinogen, and plasma osmolality. Most of the above parameters were stable during the full course of support. Compared with baseline, statistically significant differences during the entire period of implantation were only found in: hematocrit (p<0.001), hemoglobin (p<0.005), red blood cell (RBC) count (p<0.001), and whole blood viscosity (p<0.01). Plasma viscosity and ODI were mostly stable during the period of implantation. In some animals, an acute increase in fibrinogen concentration, plasma and blood viscosity, and a decrease in ODI were found to be early signs of the onset of infection. A small (10%) decrease in deformability of RBCs was found during the first 2 weeks after implantation. This alteration in RBC deformability was highly correlated (r = 0.793) with changes in total plasma protein concentration that fell more than 15% (p<0.001) during the same period. Mechanical fragility of RBCs was found to be slightly increased after implantation. Plasma free hemoglobin remained close to baseline level (p>0.2). After the first 2 weeks of the postoperative period, pump performing parameters for all animals were consistent and stable. In general, the Nimbus/UOP Axial Flow Pump demonstrated basic reliability and biocompatibility and did not produce significant alterations in the mechanical properties of blood or animal health status. The pump provided adequate hemodynamics and was well tolerated by the experimental animal for periods as long as 7.5 months. Monitoring rheologic parameters of blood is very helpful for evaluation of health during heart-assist device application.

Primary care for people with disabilities

People with disabilities are a unique population. Although there have been great advances in their care, access to reliable and consistent primary health care remains a difficult issue for many of these patients after discharge from medical rehabilitation units. Many of these health care needs are not unique to this patient population, but become compounded or exacerbated in people with disabilities. The effects of physical impairments on these patients' health need to be recognized. Specific attention must be paid to prevent the occurrence of secondary disabilities, which can drastically affect their independence. Ultimately, proper attention to the health care needs of people with disabilities will result in greater independence and improved health among this population.

Asymptotic bias and efficiency in case-control studies of candidate genes and gene-environment interactions: basic family designs

Case-control designs that use population controls are compared with those that use controls selected from their relatives (i.e., siblings, cousins, or "pseudosibs" based on parental alleles) for estimating the effect of candidate genes and gene-environment interactions. The authors first evaluate the asymptotic bias in relative risk estimates resulting from using population controls when there is confounding due to population stratification. Using siblings or pseudosibs as controls completely addresses this issue, whereas cousins provide only partial protection from population stratification. Next, they show that the conventional conditional likelihood for matched case-control studies can give asymptotically biased effect estimates when applied to the pseudosib approach; the asymptotic bias is toward the null and disappears with disease rarity. They show how to reparameterize the pseudosib likelihood so this approach gives consistent effect estimates. They then show that the designs using population or pseudosib controls are generally the most efficient for estimating the main effect of a candidate gene, followed in efficiency by the design using cousins. Finally, they show that the design using sibling controls can be quite efficient when studying gene-environment interactions. In addition to asymptotic bias and efficiency issues, family-based designs might benefit from a higher motivation to participate among cases' relatives, but these designs have the disadvantage that many potential cases will be excluded from study by having no available controls.

A study of twelve Southern California communities with differing levels and types of air pollution. II. Effects on pulmonary function

To study the possible chronic respiratory effects of air pollutants, we designed and initiated a 10-yr prospective study of Southern California public schoolchildren living in 12 communities with different levels and profiles of air pollution. The design of the study, exposure assessment methods, and survey methods and results related to respiratory symptoms and conditions are described in the accompanying paper. Pulmonary function tests were completed on 3,293 subjects. We evaluated cross-sectionally the effects of air pollution exposures based on data collected in 1986-1990 by existing monitoring stations and data collected by our study team in 1994. Expected relationships were seen between demographic, physical, and other environmental factors and pulmonary function values. When the data were stratified by sex, an association was seen between pollution levels and lower pulmonary function in female subjects, with the associations being stronger for the 1994 exposure data than the 1986-1990 data. After adjustment, PM10, PM2.5, and NO2 were each significantly associated with lower FVC, FEV1, and maximal midexpiratory flow (MMEF); acid vapor with lower FVC, FEV1, peak expiratory flow rate (PEFR), and MMEF; and O3 with lower PEFR and MMEF. Effects were generally larger in those girls spending more time outdoors. Stepwise regression of adjusted pulmonary function values for girls in the 12 communities showed that NO2 was most strongly associated with lower FVC (r = -0.74, p < 0.01), PM2.5 with FEV1 (r = -0.72, p < 0.01), O3 with PEFR (r = -0.75, p < 0.005), and PM2.5 with MMEF (r = -0.80, p < 0.005). There was a statistically significant association between ozone exposure and decreased FVC and FEV1 in girls with asthma. For boys, significant associations were seen between peak O3 exposures and lower FVC and FEV1, but only in those spending more time outdoors. These findings underline the importance of follow-up of this cohort.

A study of twelve Southern California communities with differing levels and types of air pollution. I. Prevalence of respiratory morbidity

To study possible chronic respiratory effects of air pollutants, we initiated a 10-yr prospective cohort study of Southern California children, with a study design focused on four pollutants: ozone, particulate matter, acids, and nitrogen dioxide (NO2). Twelve demographically similar communities were selected on the basis of historic monitoring information to represent extremes of exposure to one or more pollutants. In each community, about 150 public school students in grade 4, 75 in grade 7, and 75 in grade 10 were enrolled through their classrooms. Informed consent and written responses to surveys about students' lifetime residential histories, historic and current health status, residential characteristics, and physical activity were obtained with the help of the parents. In the first testing season, 3,676 students returned questionnaires. We confirmed associations previously reported between respiratory morbidity prevalence and the presence of personal, demographic, and residential risk factors. Rates of respiratory illness were higher for males, those living in houses with pets, pests, mildew, and water damage, those whose parents had asthma, and those living in houses with smokers. Wheeze prevalence was positively associated with levels of both acid (odds ratio [OR] = 1.45; 95% confidence interval [CI], 1.14-1.83) and NO2 (OR = 1.54; 95% CI, 1.08-2.19) in boys. We conclude, based on this cross-sectional assessment of questionnaire responses, that current levels of ambient air pollution in Southern California may be associated with effects on schoolchildren's respiratory morbidity as assessed by questionnaire.

A study of twelve Southern California communities with differing levels and types of air pollution. I. Prevalence of respiratory morbidity

To study possible chronic respiratory effects of air pollutants, we initiated a 10-yr prospective cohort study of Southern California children, with a study design focused on four pollutants: ozone, particulate matter, acids, and nitrogen dioxide (NO2). Twelve demographically similar communities were selected on the basis of historic monitoring information to represent extremes of exposure to one or more pollutants. In each community, about 150 public school students in grade 4, 75 in grade 7, and 75 in grade 10 were enrolled through their classrooms. Informed consent and written responses to surveys about students' lifetime residential histories, historic and current health status, residential characteristics, and physical activity were obtained with the help of the parents. In the first testing season, 3,676 students returned questionnaires. We confirmed associations previously reported between respiratory morbidity prevalence and the presence of personal, demographic, and residential risk factors. Rates of respiratory illness were higher for males, those living in houses with pets, pests, mildew, and water damage, those whose parents had asthma, and those living in houses with smokers. Wheeze prevalence was positively associated with levels of both acid (odds ratio [OR] = 1.45; 95% confidence interval [CI], 1.14-1.83) and NO2 (OR = 1.54; 95% CI, 1.08-2.19) in boys. We conclude, based on this cross-sectional assessment of questionnaire responses, that current levels of ambient air pollution in Southern California may be associated with effects on schoolchildren's respiratory morbidity as assessed by questionnaire.