Joint Effects Model Research Articles

Effects ofIL-10Haplotype and Atomic Bomb Radiation Exposure on Gastric Cancer Risk

Gastric cancer (GC) is one of the cancers that reveal increased risk of mortality and incidence in atomic bomb survivors. The incidence of gastric cancer in the Life Span Study cohort of the Radiation Effects Research Foundation (RERF) increased with radiation dose (gender-averaged excess relative risk per Gy = 0.28) and remains high more than 65 years after exposure. To assess a possible role of gene-environment interaction, we examined the dose response for gastric cancer incidence based on immunosuppression-related IL-10 genotype, in a cohort study with 200 cancer cases (93 intestinal, 96 diffuse and 11 other types) among 4,690 atomic bomb survivors participating in an immunological substudy. Using a single haplotype block composed of four haplotype-tagging SNPs (comprising the major haplotype allele IL-10-ATTA and the minor haplotype allele IL-10-GGCG, which are categorized by IL-10 polymorphisms at -819A>G and -592T>G, +1177T>C and +1589A>G), multiplicative and additive models for joint effects of radiation and this IL-10 haplotyping were examined. The IL-10 minor haplotype allele(s) was a risk factor for intestinal type gastric cancer but not for diffuse type gastric cancer. Radiation was not associated with intestinal type gastric cancer. In diffuse type gastric cancer, the haplotype-specific excess relative risk (ERR) for radiation was statistically significant only in the major homozygote category of IL-10 (ERR = 0.46/Gy, P = 0.037), whereas estimated ERR for radiation with the minor IL-10 homozygotes was close to 0 and nonsignificant. Thus, the minor IL-10 haplotype might act to reduce the radiation related risk of diffuse-type gastric cancer. The results suggest that this IL-10 haplotyping might be involved in development of radiation-associated gastric cancer of the diffuse type, and that IL-10 haplotypes may explain individual differences in the radiation-related risk of gastric cancer.

Synergy between particles and nitrogen dioxide on emergency hospital admissions for cardiac diseases in Hong Kong

Ambient air pollution is a complex mixture of particles and gaseous pollutants. Epidemiological studies are moving toward a multipollutant approach, requiring an understanding of possible interactions among the pollutants. We aim to estimate the joint effects of particles with an aerodynamic diameter less than 10 μm (PM10) and nitrogen dioxide (NO2) on emergency hospital admissions for cardiac diseases, and to explore the possible interactions between PM10 and NO2. We collected daily time series data from 1998 to 2007 on emergency hospital admissions for cardiac diseases in Hong Kong, as well as PM10 and NO2 concentrations. Generalized additive Poisson model was used to examine the relationship between air pollution and hospital admissions. We then used three parallel time series approaches (bivariate response surface model, joint effect model and parametric stratified model) to explore the possible interactions between PM10 and NO2. Results showed the greatest joint effect of PM10 and NO2 on emergency cardiac hospitalizations when PM10 and NO2 concentrations were both at high levels. The effect of PM10 was significantly greatest on the days with high NO2 level, and vice versa. A 10 μg/m(3) increase of lag0 PM10 and NO2 was associated with an increase of emergency cardiac hospitalizations by 0.55% (95% CI: 0.29-0.80%) and 1.20% (95% CI: 0.87-1.53%) respectively, when the other pollutant was at high level. We found consistent synergistic interaction between PM10 and NO2 on emergency cardiac hospitalizations in Hong Kong. These findings contribute to the development of a new paradigm for multipollutant air quality management.

Abstract MP86: The Joint Effect of Outdoor Recreational Activity and 25-Hydroxyvitamin D on Cardiovascular Mortality in THE NHANES III Population

Purpose Recreational physical activity (PA) reduces the risk of cardiovascular disease (CVD) morbidity and mortality. Outdoor-based recreational physical activities (ORA) have been reported to be associated with elevated 25(OH)D levels. We investigate the joint effects of frequent ORA and 25(OH)D levels on the risk of CVD mortality and the modifying effects of 25(OH)D. Methods Our sample consisted of 13,031 nationally representative adults (20 - 90 years old) free from CVD and cancer at baseline in the NHANES III (1988 - 1994) linked mortality dataset with follow-up mortality data through 2006. CVD mortality was based on reported deaths with corresponding ICD-10 codes for CVD as underlying cause of death. ORA was defined as self-reported participation in recreational physical activities considered to have occurred outdoors in the past month. Time to CVD mortality was estimated from multivariable adjusted Cox proportional hazards (CPH) models. A joint effects model was used in estimating multiplicative and additive interaction between ORA and 25(OH)D. Results A crude unweighted CVD mortality rate of 7.4% (964/13,031) occurred during a median follow-up of 14.33 years. Frequency of ORA <5 in the past month (HR=1.38, 95%CI:1.09 - 1.75) and 25(OH)D <30 ng/mL (HR=1.28, 95%CI:1.01 - 1.60) were associated with increased risk of CVD mortality compared to ORA ≥5 and 25(OH)D ≥30 ng/mL respectively, in a multivariable adjusted CPH model. In the joint effects model, frequency of ORA <5 and 25(OH)D <30 ng/mL (HR=1.81, 95%CI:1.05 - 3.10) and frequency of ORA <5 and 25(OH)D ≥30 ng/mL (HR=1.33, 95%CI:1.02 - 1.73) were associated with elevated risk of CVD mortality compared to the joint effects of ORA ≥5 and 25(OH)D ≥30 ng/mL. The joint effects model indicated the presence of multiplicative interaction. The synergy index, 1.52 (95%CI:0.31 - 7.41) suggested presence of additive interaction even though not statistically significant. Conclusion Lower frequency of ORA and serum 25(OH)D levels were jointly associated with elevated risk of CVD mortality. Serum 25(OH)D modified the risk of CVD mortality associated with lower frequency of outdoor-based recreational activities.

Effects of Radiation and Lifestyle Factors on Risks of Urothelial Carcinoma in the Life Span Study of Atomic Bomb Survivors

Among the Life Span Study (LSS) of Atomic-bomb survivors, recent estimates showed that unspecified bladder cancer had high radiation sensitivity with a notably high female-to-male excess relative risk (ERR) per radiation dose ratio and were the only sites for which the ERR did not decrease with attained age. These findings, however, did not consider lifestyle factors, which could potentially confound or modify the risk estimates. This study estimated the radiation risks of the most prevalent subtype of urinary tract cancer, urothelial carcinoma, while accounting for smoking, consumption of fruit, vegetables, alcohol and level of education (a surrogate for socioeconomic status). Eligible study subjects included 105,402 (males = 42,890) LSS members who were cancer-free in 1958 and had estimated radiation doses. Members were censored due to loss of follow-up, incident cancer of another type, death, or the end of calendar year 2001. Surveys (by mail or clinical interview) gathered lifestyle data periodically for 1963-1991. There were 63,827 participants in one or more survey. Five hundred seventy-three incident urothelial carcinoma cases occurred, of which 364 occurred after lifestyle information was available. Analyses were performed using Poisson regression methods. The excess relative risk per weighted gray unit (the gamma component plus 10 times the neutron component, Gy(w)) was 1.00 (95% CI: 0.43-1.78) but the risks were not dependent upon age at exposure or attained age. Lifestyle factors other than smoking were not associated with urothelial carcinoma risk. Neither the magnitude of the radiation ERR estimate (1.00 compared to 0.96), nor the female-to-male (F:M) ERR/Gy(w) ratio (3.2 compared to 3.4) were greatly changed after accounting for all lifestyle factors. A multiplicative model of gender-specific radiation and smoking effects was the most revealing though there was no evidence of significant departures from either the additive or multiplicative joint effect models. Among the LSS cohort members with doses greater than 0.005 Gy(w) (average dose 0.21 Gy(w)), the attributable fraction of urothelial carcinoma due to radiation was 7.1% in males and 19.7% in females. Among current smokers, the attributable fraction of urothelial carcinoma due to smoking was 61% in males and 52% in females. Relative risk estimates of smoking risk were approximately two for smokers compared to nonsmokers. After adjustment for lifestyle factors, gender-specific radiation risks and the F:M ERR/Gy(w), the ratios of excess urothelial carcinoma risk were similar to the estimates without adjusting for lifestyle factors. Smoking was the primary factor responsible for excess urothelial carcinoma in this cohort. These findings led us to conclude that the radiation risk estimates of urothelial carcinoma do not appear to be strongly confounded or modified by smoking, consumption of alcohol, fruits, or vegetables, or level of education.

Single nucleotide polymorphisms in the matrix metalloproteinase gene family and the frequency and duration of gastroesophageal reflux disease influence the risk of esophageal adenocarcinoma

The matrix metalloproteinase (MMP) family of proteins mediates various cellular pathways, including apoptosis and angiogenesis. Polymorphisms of MMP genes are associated with increased esophageal adenocarcinoma (EAC) risk. Gastroesophageal reflux disease (GERD) is an established EAC risk factor. We examined whether MMP polymorphism-EAC risk is modified by GERD. In total, 309 EAC patients and 279 frequency-matched healthy controls underwent MMP1 1G/2G, MMP3 6A/5A, MMP12 -82A/G and MMP12 1082A/G genotyping. Questionnaires collected GERD history. EAC risk was analyzed using logistic regression, adjusted for key covariates and stratified by GERD. Joint effects models explored GERD severity and duration, whereas additional models explored genotype-GERD interactions in EAC risk. We determined that each MMP1 and MMP3 minor (variant) allele was independently associated with increased EAC risk (adjusted odds ratio (AOR) 3.2, 95% confidence interval (CI) 2.0-5.1, p < 0.001 and AOR 1.8, 95% CI 1.1-2.7, p = 0.01, respectively) only among those with GERD but not in GERD-free individuals (all p = nonsignificant). There were significant interactions between the MMP1 variants and the presence of GERD (p = 0.002) and between MMP3 variants and GERD (p = 0.04). There was an equally strong interaction between cumulative GERD severity and MMP1 (p = 0.002). The AOR of each variant allele was 14.9 (95% CI 1.6-136) for individuals with severe GERD, 1.7 (95% CI 1.0-2.7) for mild-moderate GERD and 0.98 (95% CI 0.7-1.4) for those without GERD. This was further reflected in separate analyses of frequency and duration of GERD. In conclusion, MMP1 1G/2G (and possibly MMP3 6A/5A) polymorphisms alter EAC risk differentially for GERD and GERD-free individuals.

Longitudinal replication studies of GWAS risk SNPs influencing body mass index over the course of childhood and adulthood.

Genome-wide association studies (GWAS) have identified multiple common variants associated with body mass index (BMI). In this study, we tested 23 genotyped GWAS-significant SNPs (p-value<5*10-8) for longitudinal associations with BMI during childhood (3–17 years) and adulthood (18–45 years) for 658 subjects. We also proposed a heuristic forward search for the best joint effect model to explain the longitudinal BMI variation. After using false discovery rate (FDR) to adjust for multiple tests, childhood and adulthood BMI were found to be significantly associated with six SNPs each (q-value<0.05), with one SNP associated with both BMI measurements: KCTD15 rs29941 (q-value<7.6*10-4). These 12 SNPs are located at or near genes either expressed in the brain (BDNF, KCTD15, TMEM18, MTCH2, and FTO) or implicated in cell apoptosis and proliferation (FAIM2, MAP2K5, and TFAP2B). The longitudinal effects of FAIM2 rs7138803 on childhood BMI and MAP2K5 rs2241423 on adulthood BMI decreased as age increased (q-value<0.05). The FTO candidate SNPs, rs6499640 at the 5 ′-end and rs1121980 and rs8050136 downstream, were associated with childhood and adulthood BMI, respectively, and the risk effects of rs6499640 and rs1121980 increased as birth weight decreased. The best joint effect model for childhood and adulthood BMI contained 14 and 15 SNPs each, with 11 in common, and the percentage of explained variance increased from 0.17% and 9.0*10−6% to 2.22% and 2.71%, respectively. In summary, this study evidenced the presence of long-term major effects of genes on obesity development, implicated in pathways related to neural development and cell metabolism, and different sets of genes associated with childhood and adulthood BMI, respectively. The gene effects can vary with age and be modified by prenatal development. The best joint effect model indicated that multiple variants with effects that are weak or absent alone can nevertheless jointly exert a large longitudinal effect on BMI.

Acceptance criteria for urban dispersion model evaluation

The authors suggested acceptance criteria for rural dispersion models’ performance measures in this journal in 2004. The current paper suggests modified values of acceptance criteria for urban applications and tests them with tracer data from four urban field experiments. For the arc-maximum concentrations, the fractional bias should have a magnitude 0.3. For all data paired in space, for which a threshold concentration must always be defined, the normalized absolute difference should be <0.50, when the threshold is three times the instrument’s limit of quantification (LOQ). An overall criterion is then applied that the total set of acceptance criteria should be satisfied in at least half of the field experiments. These acceptance criteria are applied to evaluations of the US Department of Defense’s Joint Effects Model (JEM) with tracer data from US urban field experiments in Salt Lake City (U2000), Oklahoma City (JU2003), and Manhattan (MSG05 and MID05). JEM includes the SCIPUFF dispersion model with the urban canopy option and the urban dispersion model (UDM) option. In each set of evaluations, three or four likely options are tested for meteorological inputs (e.g., a local building top wind speed, the closest National Weather Service airport observations, or outputs from numerical weather prediction models). It is found that, due to large natural variability in the urban data, there is not a large difference between the performance measures for the two model options and the three or four meteorological input options. The more detailed UDM and the state-of-the-art numerical weather models do provide a slight improvement over the other options. The proposed urban dispersion model acceptance criteria are satisfied at over half of the field experiments.

The influence of physicians on colorectal cancer screening behavior

Our aims were to determine clinical factors associated with colorectal cancer (CRC) screening and to evaluate the relative role of patient contact with physicians and the quality of these patient-physician interactions in affecting screening. Screening-eligible patients were identified from the Health Information National Trends Survey. Determinants of CRC screening were assessed with logistic regression, and a joint effects model that considered the frequency and quality of contact with physicians was developed to explore their influence on screening. There were 4,615 respondents of whom only 66% reported receiving CRC screening. Older age, personal history of non-CRC, family history of any cancer, high-income earners, individuals who visited their physicians ≥5 times per year, and those who rated the interactions with their physicians highly were more likely to be screened (all p<0.05). The joint effects model revealed that quality rather than frequency of physician contact was a stronger predictor of CRC screening, but the odds of screening was highest for those who experienced both frequent and high-quality interactions with their physicians. Contact with physicians and the quality of this interaction are associated with screening behavior. Interventions to improve these provider-related factors may promote CRC screening.

Inference From a Multiplicative Model of Joint Genetic Effects for Ovarian Cancer Risk

Inference From a Multiplicative Model of Joint Genetic Effects for Ovarian Cancer Risk

Abstract A7: Using haplotype analysis to find significant associations between genes and Hodgkin's disease

Abstract Background: With increasing amounts of genes available for study, more opportunities are available to discover key associations between genetic factors and disease. In a previous study on Hodgkin disease, we observed powerful positive associations between genes on chromosomes 3 and 19. In this study, we expanded the previous analyses to include 62 single nucleotide polymorphisms (SNPs) in DNA repair and inflammation pathway genes located throughout the genome and evaluated possible associations for Hodgkin disease by inferring haplotypes at the individual gene level. Methods: Genetic and epidemiological data were obtained from a case-control study conducted at M.D. Anderson Cancer Center between 1987 and 1992 including 200 cases and 220 controls. Haplotypes were initially inferred with Haploview using linkage disequilibrium plots, and differences in haplotypes between cases and controls were determined with PHASE. Linear modeling with haplotypes, through both joint and separate effects haplotype modeling, with sex, race, smoking status, and age as confounders, were conducted with Haplo.stats. A joint-effects linear model allows each haplotype to be compared to the most frequent haplotype. A separate-effects linear model compares a haplotype to all of the other haplotypes possible for study. Results: With the joint effects haplotype model, some significant haplotype associations with Hodgkin disease were observed with DNA repair gene XPC on chromosome 3 and inflammation pathway gene ILR4 on Chromosome 16. For DNA repair gene XPC, susceptible associations with Hodgkin disease were discovered with the use of an additive genetic model with haplotype CT from SNPs rs2228001 (XPC 499 A&amp;gt;C) and rs2228000 (XPC 939 C&amp;gt;T) (OR = 1.49, 95% CI = 1.03–2.16) and a dominant genetic model with the same haplotype (OR = 1.75, 95% CI = 1.15–2.13). For inflammation pathway gene ILR4, protective associations with Hodgkin disease were discovered with the use of an additive genetic model with haplotype TC from SNPs rs1805012 (XPC 499 T&amp;gt;C) and rs1805015 (XPC 939 T&amp;gt;C) (OR = 0.63, 95% CI = 0.33–0.99) and a dominant genetic model with the same haplotype (OR = 0.48, 95% CI = 0.26–0.88). The separate effects haplotype model also highlighted associations between haplotypes and Hodgkin disease on these same genes. Other significant associations between haplotypes and Hodgkin disease were observed on chromosomes 5 with inflammation pathway gene IL4 and chromosome 19 with DNA repair gene. Conclusions: The basis for haplotype analysis to analyze the effects of linked SNPs associated with Hodgkin disease has been demonstrated. Furthermore, the interactions between specific SNPs in both the inflammation and the DNA repair pathway have been shown to play an important role in possible Hodgkin disease development. By targeting specific aspects of the genome that show either an increase or decrease in Hodgkin risk, identification of high risk individuals could be achieved. Citation Information: Cancer Prev Res 2010;3(1 Suppl):A7.

The Policy Impact of Social Movements: A Replication Through Qualitative Comparative Analysis

This article reanalyzes the data of a previous study on the policy impact of antinuclear, ecology, and peace movements in three countries with the aim of replicating its findings. Our goal is to see whether using a different analytical technique will yield similar results. The previous study used a regression approach to time-series analysis. Here, we use qualitative comparative analysis (QCA) to analyze the previous study's data. Specifically, we test the two main hypotheses based on the joint-effect model of social movement outcomes: (1) that the policy impact of social movements is conditioned by the presence of powerful allies within the institutional arenas, by the presence of a favorable public opinion, and/or by both factors simultaneously; and (2) that social movements are more likely to have policy impacts when they address issues and policy domains of low saliency. In addition, we compare the policy impact of social movements across countries. Our analysis confirms to a large extent the findings of the earlier time-series analysis, namely, the strong explanatory power of the jointeffect model of social movement outcomes and the varying impact of different movements on public policy.

An association analysis of Alzheimer disease candidate genes detects an ancestral risk haplotype clade in ACE and putative multilocus association between ACE, A2M, and LRRTM3

Alzheimer's disease (AD) is the most common form of progressive dementia in the elderly. It is a neurodegenerative disorder characterized by the neuropathologic findings of neurofibrillary tangles and amyloid plaques that accumulate in vulnerable brain regions. AD etiology has been studied by many groups, but since the discovery of the APOE epsilon4 allele, no further genes have been mapped conclusively to late-onset AD (LOAD). In this study, we examined genetic association with LOAD susceptibility in 738 Caucasian families (4,704 individuals) and an independent case-control dataset with 296 cases and 566 controls exploring 11 candidate genes (47 SNPs common to both samples). In addition to tests for main effects and haplotypes, the MDR-PDT was used to search for gene-gene interactions in the family data. We observed significant haplotype effects in ACE in family and case-control samples using standard and cladistic haplotype models. ACE was also part of significant 2 and 3-locus MDR-PDT joint effects models with Alpha-2-Macroglobulin (A2M), which mediates the clearance of Abeta, and Leucine-Rich Repeat Transmembrane-3 (LRRTM3), a nested gene in Alpha-3 Catenin (CTNNA3) which binds Presenilin-1. This result did not replicate in the case-control sample, and may not be a true positive. These genes are related to Abeta clearance; thus this constellation of effects might constitute an axis of susceptibility for LOAD. The consistent ACE haplotype result between independent family-based and unrelated case-control datasets is strong evidence in favor of ACE as a susceptibility locus for AD, and replicates results from several other studies in a large sample.

Epidermal growth factor A61G gene polymorphism, gastroesophageal reflux disease and esophageal adenocarcinoma risk

Single-nucleotide polymorphisms of key cancer genes, such as EGF A61G, are associated with an elevated risk of esophageal adenocarcinoma (EAC). As gastroesophageal reflux disease (GERD) is an established risk factor for EAC, we evaluated whether the association between epidermal growth factor (EGF) polymorphism and EAC development is altered by the presence of GERD. EGF genotyping of DNA samples was performed and GERD history was collected for 309 EAC patients and 275 matched healthy controls. Associations between genotypes and EAC risk were evaluated using adjusted logistic regression. Genotype-GERD relationships were explored using analyses stratified by GERD history and joint effects models that considered severity and duration of GERD symptoms. EGF variants (A/G or G/G) were more common (P = 0.02) and GERD was more prevalent (P < 0.001) in cases than in controls. When compared with the EGF wild-type A/A genotype, the G/G variant was associated with a substantial increase in EAC risk among individuals with GERD [Odds ratio 9.7; 95% confidence interval (CI), 3.8-25.0; P < 0.001] and a slight decrease in risk for GERD-free individuals (odds ratio 0.4; 95% CI = 0.22-0.90; P = 0.02). In the joint effects models, the odds of EAC was also highest for G/G patients (when compared with A/A) who either experienced frequent GERD of more than once per week (odds ratio 21.8; 95% CI = 5.1-94.0; P < 0.001) or suffered GERD for longer than 15 years (odds ratio 22.4; 95% CI = 6.5-77.6; P < 0.001). There was a highly significant interaction between the G/G genotype and the presence of GERD (P < 0.001). EGF A61G polymorphism may alter EAC susceptibility through an interaction with GERD.

Epidermal growth factor (EGF) gene polymorphism, gastroesophageal reflux disease (GERD), and esophageal adenocarcinoma (EAC) risk

11029 Background: Single nucleotide polymorphisms (SNPs) of key cancer genes, such as EGF A61G, are associated with an elevated risk of EAC, but the lack of full penetrance indicates that the effects of these SNPs on esophageal carcinogenesis are modified by additional genetic or environmental variables. Since GERD is an established risk factor for EAC, we evaluated whether the association between EGF polymorphism and EAC development is altered by the presence of GERD. Methods: EGF genotyping of DNA samples was performed and GERD history was collected for 309 EAC patients and 275 matched healthy controls. Associations between genotypes and EAC risk were examined with adjusted logistic regression. Genotype-GERD relationships were explored using analyses stratified by GERD history and joint effects models that considered severity and duration of GERD symptoms. Results: Baseline characteristics were comparable between cases and controls except that EGF variants (A/G or G/G) were more common (p=0.02) and GERD was more prevalent (p&lt;0.001) in cases than in controls. When compared to the EGF wild type A/A genotype, the G/G variant was associated with an increased risk of EAC (OR 1.9; 95% CI, 1.2–3.0; p=0.007). Stratified analyses revealed that the G/G variant contributed to a substantial increase in EAC risk among individuals with GERD, but a slight decrease in risk for GERD-free individuals (see table). In the joint effects models, the odds of EAC was also highest for G/G patients who either experienced frequent GERD of more than once per week (OR 21.8; 95% CI, 5.1–94.0; p&lt;0.001) or suffered GERD for longer than 15 years (OR 22.4; 95% CI, 6.5–77.6; p&lt;0.001). There was a highly significant interaction between the G/G genotype and the presence of GERD (p&lt;0.001). Conclusions: EGF A61G polymorphism exerts its effect on EAC susceptibility through an interaction with GERD. Performing EGF genotyping for patients with severe or longstanding GERD can help to identify individuals at the greatest risk of EAC. [Table: see text] No significant financial relationships to disclose.

Less is more, except when less is less: Studying joint effects

Most diseases are complex in that they are caused by the joint action of multiple factors, both genetic and environmental. Over the past few decades, the mathematical convenience of logistic regression has served to enshrine the multiplicative model, to the point where many epidemiologists believe that departure from additivity on a log scale implies that two factors interact in causing disease. Other terminology in epidemiology, where students are told that inequality of relative risks across levels of a second factor should be seen as “effect modification,” reinforces an uncritical acceptance of multiplicative joint effect as the biologically meaningful no-interaction null. Our first task, when studying joint effects, is to understand the limitations of our definitions for “interaction,” and recognize that what statisticians mean and what biologists might want to mean by interaction may not coincide. Joint effects are notoriously hard to identify and characterize, even when asking a simple and unsatisfying question, like whether two effects are log-additive. The rule of thumb for such efforts is that a factor-of-four sample size is needed, compared with that needed to demonstrate main effects of either genes or exposures. So strategies have been devised that focus on the most informative individuals, either through risk-based sampling for a cohort, or case–control sampling, extreme phenotype sampling, pooling, two-stage sampling, exposed-only, or case-only designs. These designs gain efficiency, but at a cost of flexibility in models for joint effects. A relatively new approach avoids population controls by genotyping case–parent triads. Because it requires parents, the method works best for diseases with onset early in life. With this design, the role of autosomal genetic variants is assessed by in effect treating the nontransmitted parental alleles as controls for affected offspring. Despite advantages for looking at genetic effects, the triad design faces limitations when examining joint effects of genetic and environmental factors. Because population-based controls are not included, main effects for exposures cannot be estimated, and consequently one only has access to inference related to a multiplicative null. We have proposed a hybrid approach that offers the best features of both case–parent and case–control designs. Through genotyping of parents of population-based controls and assuming Mendelian transmission, power is markedly enhanced. One can also estimate main effects for exposures and now flexibly assess models for joint effects.

How to confirm identified toxicants in effect-directed analysis

Due to the production and use of a multitude of chemicals in modern society, waters, sediments, soils and biota may be contaminated with numerous known and unknown chemicals that may cause adverse effects on ecosystems and human health. Effect-directed analysis (EDA), combining biotesting, fractionation and chemical analysis, helps to identify hazardous compounds in complex environmental mixtures. Confirmation of tentatively identified toxicants will help to avoid artefacts and to establish reliable cause-effect relationships. A tiered approach to confirmation is suggested in the present paper. The first tier focuses on the analytical confirmation of tentatively identified structures. If straightforward confirmation with neat standards for GC-MS or LC-MS is not available, it is suggested that a lines-of-evidence approach is used that combines spectral library information with computer-based structure generation and prediction of retention behaviour in different chromatographic systems using quantitative structure-retention relationships (QSRR). In the second tier, the identified toxicants need to be confirmed as being the cause of the measured effects. Candidate components of toxic fractions may be selected based, for example, on structural alerts. Quantitative effect confirmation is based on joint effect models. Joint effect prediction on the basis of full concentration-response plots and careful selection of the appropriate model are suggested as a means to improve confirmation quality. Confirmation according to the Toxicity Identification Evaluation (TIE) concept of the US EPA and novel tools of hazard identification help to confirm the relevance of identified compounds to populations and communities under realistic exposure conditions. Promising tools include bioavailability-directed extraction and dosing techniques, biomarker approaches and the concept of pollution-induced community tolerance (PICT). [figure: see text]

A longitudinal study of alcohol use and antisocial behaviour in young people

Aims: To examine the direction of causation between young people's antisocial behaviour and alcohol (mis)use in the longer and shorter term, together with their joint effects on alcohol-related trouble. Methods: A longitudinal study (2586 pupils) supplied data, allowing exploration of the causal effects of alcohol (mis)use and antisocial behaviour between ages 11 and 15, using structural equation models of longer and shorter-term relationships and joint-effects models in respect of alcohol-related trouble at age 15. This method allowed us to evaluate which of three hypotheses, described as ‘disinhibition’ [alcohol (mis)use causes or facilitates antisocial behaviour], ‘susceptibility’ [antisocial behaviour causes alcohol (mis)use] or ‘reciprocal’ [alcohol (mis)use causes antisocial behaviour and the reverse] receives most support, both overall and by gender, social class, and drinking context. Results: Overall, the results support the susceptibility hypothesis, particularly in the longer-term models. There is no support for ‘pure’ disinhibition. However, in the shorter-term and joint-effects models (i.e. as the time lag becomes shorter), there is evidence that in some gender, social class, or drinking contexts, in addition to antisocial behaviour causing alcohol (mis)use, the reverse also applies. Conclusions: Antisocial behaviour is the main predictor of alcohol (mis)use and alcohol-related trouble, with alcohol (mis)use impacting only modestly on antisocial behaviour and alcohol-related trouble in the shorter term.

Can DAGs Clarify Effect Modification?

The system proposed by VanderWeele and Robins for categorization of effect modifiers that are causal nodes in a directed acyclic graph (DAG) was not intended to empower DAGs to fully represent complex interactions among causes. However, once one has algebraically identified effect modifiers, the DAG implies a role for them. The limitations of epidemiologic definitions of "effect modification" are discussed, along with the implications of scale dependency for assessing interactions, where the scale can be either absolute risk, relative risk, or odds. My view is that probabilistic independence leads to the log-complement as a natural scale for interaction, but even that scale does not necessarily admit unambiguous inference. Any 2 direct causes of D are effect modifiers for each other on at least 2 scales, which can make a reasonable person question the utility of the concept. Still, etiologic models for joint effects are important, because most diseases arise through pathways involving multiple factors. I suggest an enhancement in construction of DAGs in epidemiology that includes arrow-on-arrow representations for effect modification. Examples are given, some of which depend on scale and some of which do not. An example illustrates possible biologic implications for such an effect modification DAG.

Useless Protest? A Time-Series Analysis of the Policy Outcomes of Ecology, Antinuclear, and Peace Movements in the United States, 1977-1995

I confront three models of the policy impact of social movements with data on the mobilization of ecology, antinuclear, and peace movements in the United States between 1975 and 1995 by means of time-series analysis: the direct-effect model, the indirect-effect model, and the joint-effect model. My analysis suggests that social movements have little, if any, impact on public policy and that, if they are to have an impact, it depends on the combination of overt protest activities, the type of issues they raise, and external resources such as public opinion and political alliances with institutional actors. Thus, it appears that, if they are to have a policy impact, movements need the joint occurence of mobilization, support from political allies, and public opinion favorable to the cause.

Numbers and Beyond: The Relevance of Critical Mass in Gender Research

Political scientists concerned with gender relations have long been interested in the numbers of women in national legislatures. Women make up slightly more than 50% of the world's population, yet average only 16% of the world's elected political posts. This has led to calls for action that would increase the number of women in legislatures based both on arguments of justice and on claims that an increase will substantively change decision-making processes and outcomes. Part of the debate about substantive changes in political decision making has centered on whether women in a legislature must reach a “critical mass” in order to bring about change in the political arena. The term critical mass is frequently used by politicians, the media, and academics, but can it offer insights into the influence of gender on political processes and outcomes? In this essay, I argue that critical mass is only useful if we discard the belief that a single proportion holds the key to all representation needs of women and if we discard notions that numbers alone bring about substantive changes in policy processes and outcomes. I use a longitudinal textual analysis of New Zealand parliamentary debates to begin development of a joint-effect model that can better explain the factors that aid (or hinder) the substantive representation of women.