ABSTRACT
BACKGROUND: Globally, the ages at pubertal onset for girls and boys have been decreasing during recent decades, partly attributed to excess body fat accumulation. However, a growing body of literature has recognized that endocrine disrupting chemicals (EDCs) may play an important role in this global trend, but the association has not yet been fully established. OBJECTIVE AND RATIONALE: EDCs can interfere with normal hormone function and metabolism and play a role in pubertal onset. We aimed to systematically identify and evaluate the current evidence on the timing of pubertal onset in girls and boys following prenatal or postnatal exposures to xenobiotic EDCs. SEARCH METHODS: Following PRISMA guidelines, we performed a systematic literature search of original peer-reviewed publications in the PubMed database through a block search approach using a combination of index MeSH and free text search terms. Publications were considered if they covered biomarkers of prenatal or postnatal exposures to xenobiotic EDCs (European Commission's list of category 1 EDCs) measured in maternal or child biospecimen and pubertal onset defined by the progression of the following milestones (and assessed in terms of the following measures): menarche (age), thelarche (Tanner staging) and pubarche (Tanner staging), in girls, and genital stage (Tanner staging), testicular volume (ml) and pubarche (Tanner staging), in boys. OUTCOMES: The literature search resulted in 703 references, of which we identified 52 publications fulfilling the eligibility criteria for the qualitative trend synthesis and 23 publications for the meta-analysis. The qualitative trend synthesis provided data on 103 combinations of associations between prenatal or postnatal exposure to EDC compounds groups and puberty outcomes and the meta-analysis enabled 18 summary risk estimates of meta-associations. WIDER IMPLICATIONS: Statistically significant associations in the qualitative trend synthesis suggested that postnatal exposure to phthalates may be associated with earlier thelarche and later pubarche. However, we did not find consistent evidence in the meta-analysis for associations between timing of pubertal onset in girls and boys and exposures to any of the studied xenobiotic EDCs. We were not able to identify specific pre- or postnatal windows of exposure as particularly critical and susceptible for effects of EDCs. Current evidence is subject to several methodological challenges and inconsistencies and evidence on specific exposure-outcome associations remains too scarce to firmly confirm EDC exposure as a risk factor for changes in age of pubertal onset in the general child population. To create a more uniform foundation for future comparison of evidence and to strengthen pooled studies, we recommend the use of more standardized approaches in the choice of statistical analyses, with exposure transformations, and in the definitions and assessments of puberty outcomes. The impact of mixtures of EDC exposures on the association also remains unestablished and would be valuable to elucidate for prenatal and postnatal windows of exposure. Future large, longitudinal epidemiological studies are needed to clarify the overall association.
Subject(s)
Endocrine Disruptors , Child , Endocrine Disruptors/adverse effects , Female , Humans , Longitudinal Studies , Male , Menarche , Pregnancy , Puberty , Xenobiotics/adverse effectsABSTRACT
Mediation analysis has mostly been conducted with mean regression models. With this approach modeling means, formulae for direct and indirect effects are based on changes in means, which may not capture effects that occur in units at the tails of mediator and outcome distributions. Individuals with extreme values of medical endpoints are often more susceptible to disease and can be missed if one investigates mean changes only. We derive the controlled direct and indirect effects of an exposure along percentiles of the mediator and outcome using quantile regression models and a causal framework. The quantile regression models can accommodate an exposure-mediator interaction and random intercepts to allow for longitudinal mediator and outcome. Because DNA methylation acts as a complex "switch" to control gene expression and fibrinogen is a cardiovascular factor, individuals with extreme levels of these markers may be more susceptible to air pollution. We therefore apply this methodology to environmental data to estimate the effect of air pollution, as measured by particle number, on fibrinogen levels through a change in interferon-gamma (IFN-γ) methylation. We estimate the controlled direct effect of air pollution on the qth percentile of fibrinogen and its indirect effect through a change in the pth percentile of IFN-γ methylation. We found evidence of a direct effect of particle number on the upper tail of the fibrinogen distribution. We observed a suggestive indirect effect of particle number on the upper tail of the fibrinogen distribution through a change in the lower percentiles of the IFN-γ methylation distribution.
Subject(s)
Causality , Confounding Factors, Epidemiologic , Regression Analysis , Air Pollutants/adverse effects , Air Pollution/adverse effects , Boston , Cardiovascular Diseases , Computer Simulation , Data Interpretation, Statistical , Fibrinogen , Humans , Longitudinal Studies , Particulate MatterABSTRACT
BACKGROUND: Prenatal exposure to traffic pollution has been associated with faster infant weight gain, but implications for cardiometabolic health in later childhood are unknown. METHODS: Among 1418 children in Project Viva, a Boston-area pre-birth cohort, we assessed anthropometric and biochemical parameters of cardiometabolic health in early (median age 3.3 years) and mid- (median age 7.7 years) childhood. We used spatiotemporal models to estimate prenatal and early life residential PM2.5 and black carbon exposure as well as traffic density and roadway proximity. We performed linear regression analyses adjusted for sociodemographics. RESULTS: Children whose mothers lived close to a major roadway at the time of delivery had higher markers of adverse cardiometabolic risk in early and mid-childhood. For example, total fat mass was 2.1 kg (95%CI: 0.8, 3.5) higher in mid-childhood for children of mothers who lived <50 m vs. ≥200 m from a major roadway. Black carbon exposure and traffic density were generally not associated with cardiometabolic parameters, and PM2.5 exposure during the year prior was paradoxically associated with improved cardiometabolic profile. CONCLUSIONS: Infants whose mothers lived close to a major roadway at the time of delivery may be at later risk for adverse cardiometabolic health.
Subject(s)
Air Pollutants/adverse effects , Air Pollution/adverse effects , Environmental Exposure/adverse effects , Metabolic Syndrome/epidemiology , Air Pollutants/analysis , Biomarkers/analysis , Boston , Child , Child, Preschool , Cohort Studies , Female , Humans , Infant , Male , Metabolic Syndrome/etiology , Pregnancy , Prenatal Exposure Delayed Effects , Prospective Studies , Regression AnalysisABSTRACT
Mediation analysis is a valuable approach to examine pathways in epidemiological research. Prospective cohort studies are often conducted to study biological mechanisms and often collect longitudinal measurements on each participant. Mediation formulae for longitudinal data have been developed. Here, we formalize the natural direct and indirect effects using a causal framework with potential outcomes that allows for an interaction between the exposure and the mediator. To allow different types of longitudinal measures of the mediator and outcome, we assume two generalized mixed-effects models for both the mediator and the outcome. The model for the mediator has subject-specific random intercepts and random exposure slopes for each cluster, and the outcome model has random intercepts and random slopes for the exposure, the mediator, and their interaction. We also expand our approach to settings with multiple mediators and derive the mediated effects, jointly through all mediators. Our method requires the absence of time-varying confounding with respect to the exposure and the mediator. This assumption is achieved in settings with exogenous exposure and mediator, especially when exposure and mediator are not affected by variables measured at earlier time points. We apply the methodology to data from the Normative Aging Study and estimate the direct and indirect effects, via DNA methylation, of air pollution, and temperature on intercellular adhesion molecule 1 (ICAM-1) protein levels. Our results suggest that air pollution and temperature have a direct effect on ICAM-1 protein levels (i.e. not through a change in ICAM-1 DNA methylation) and that temperature has an indirect effect via a change in ICAM-1 DNA methylation.
Subject(s)
Data Interpretation, Statistical , Models, Statistical , Aging/metabolism , DNA Methylation/physiology , Humans , Intercellular Adhesion Molecule-1/metabolismABSTRACT
BACKGROUND: Literature relating air pollution exposure to deep vein thrombosis (DVT) and pulmonary embolism (PE), despite biological plausibility, is sparse. No comprehensive study examining associations between both short- and long-term exposure to particulate matter (PM)2.5 and DVT or PE has been published. Using a novel PM2.5 prediction model, we study whether long- and short-term PM2.5 exposure is associated with DVT and PE admissions among elderly across the northeastern United States. METHODS: We estimated daily exposure of PM2.5 in each ZIP code. We investigated the long- and short-term effects of PM2.5 on DVT and PE hospital admissions. There were 453,413 DVT and 151,829 PE admissions in the study. For short-term exposure, we performed a case crossover analysis matching month and year and defined the hazard period as lag 01 (exposure of day of admission and previous day). For the long-term association, we used a Poisson regression. RESULTS: A 10-µg m(-3) increase in short-term exposure was associated with a 0.63% increase in DVT admissions (95% confidence interval [CI] = 0.03% to 1.25%) and a 6.98% (95% CI = 5.65% to 8.33%) increase in long-term exposure admissions. For PE, the associated risks were 0.38% (95% CI = -0.68% to 1.25%) and 2.67% (95% CI = 5.65% to 8.33%). These results persisted when analyses were restricted to location-periods meeting the current Environmental Protection Agency annual standard of 12 µg m(-3) . CONCLUSIONS: Our findings showed that PM2.5 exposure was associated with DVT and PE hospital admissions and that current standards are not protective of this result.
Subject(s)
Particulate Matter/toxicity , Patient Admission , Venous Thrombosis/etiology , Aged , Environmental Exposure , Female , Humans , Male , New England/epidemiology , Venous Thrombosis/epidemiologyABSTRACT
OBJECTIVES: Ambient particulate air pollution has been associated with increased risk of cardiovascular morbidity and mortality. Pathways by which particles may act involve autonomic nervous system dysfunction or inflammation, which can affect cardiac rate and rhythm. The importance of these pathways may vary by particle component or source. In an eastern US location with significant regional pollution, the authors examined the association of air pollution and odds of cardiac arrhythmia in older adults. METHODS: Thirty two non-smoking older adults were evaluated on a weekly basis for 24 weeks during the summer and autumn of 2000 with a standardised 30 minute protocol that included continuous electrocardiogram measurements. A central ambient monitoring station provided daily concentrations of fine particles (PM(2.5), sulfate, elemental carbon) and gases. Sulfate was used as a marker of regional pollution. The authors used logistic mixed effects regression to examine the odds of having any supraventricular ectopy (SVE) or ventricular ectopy (VE) in association with increases in air pollution for moving average pollutant concentrations up to 10 days before the health assessment. RESULTS: Participant specific mean counts of arrhythmia over the protocol varied between 0.1-363 for SVE and 0-350 for VE. The authors observed odds ratios for having SVE over the length of the protocol of 1.42 (95% CI 0.99 to 2.04), 1.70 (95% CI 1.12 to 2.57), and 1.78 (95% CI 0.95 to 3.35) for 10.0 microg/m3, 4.2 microg/m3, and 14.9 ppb increases in five day moving average PM2.5, sulfate, and ozone concentrations respectively. The other pollutants, including elemental carbon, showed no effect on arrhythmia. Participants reporting cardiovascular conditions (for example, previous myocardial infarction or hypertension) were the most susceptible to pollution induced SVE. The authors found no association of pollution with VE. CONCLUSION: Increased levels of ambient sulfate and ozone may increase the risk of supraventricular arrhythmia in the elderly.
Subject(s)
Air Pollutants/toxicity , Arrhythmias, Cardiac/epidemiology , Ventricular Dysfunction/epidemiology , Aged , Aged, 80 and over , Air Pollutants/analysis , Arrhythmias, Cardiac/etiology , Carbon/analysis , Carbon/toxicity , Electrocardiography , Female , Humans , Male , Middle Aged , Nitrogen Dioxide/analysis , Nitrogen Dioxide/toxicity , Ozone/analysis , Ozone/toxicity , Sulfur Dioxide/analysis , Sulfur Dioxide/toxicity , Ventricular Dysfunction/etiologyABSTRACT
AIMS: To illustrate the contribution of smoothing methods to modelling exposure-response data, Cox models with penalised splines were used to reanalyse lung cancer risk in a cohort of workers exposed to silica in California's diatomaceous earth industry. To encourage application of this approach, computer code is provided. METHODS: Relying on graphic plots of hazard ratios as smooth functions of exposure, the sensitivity of the curve to amount of smoothing, length of the exposure lag, and the influence of the highest exposures was evaluated. Trimming and data transformations were used to down-weight influential observations. RESULTS: The estimated hazard ratio increased steeply with cumulative silica exposure before flattening and then declining over the sparser regions of exposure. The curve was sensitive to changes in degrees of freedom, but insensitive to the number or location of knots. As the length of lag increased, so did the maximum hazard ratio, but the shape was similar. Deleting the two highest exposed subjects eliminated the top half of the range and allowed the hazard ratio to continue to rise. The shape of the splines suggested a parametric model with log hazard as a linear function of log transformed exposure would fit well. CONCLUSIONS: This flexible statistical approach reduces the dependence on a priori assumptions, while pointing to a suitable parametric model if one exists. In the absence of an appropriate parametric form, however, splines can provide exposure-response information useful for aetiological research and public health intervention.
Subject(s)
Lung Neoplasms/epidemiology , Models, Statistical , Occupational Diseases/epidemiology , Adult , Aged , Aged, 80 and over , Cohort Studies , Humans , Male , Middle Aged , Occupational Exposure/adverse effects , Reference Values , Risk Assessment/methods , Risk FactorsABSTRACT
We propose a new method for computing power and sample size for linear rank tests of differences between two ordered multinomial populations. The method is flexible in that it is applicable to any general alternative hypothesis and for any choice of rank scores. We show that the method, though asymptotic, closely approximates existing exact methods. At the same time it overcomes the computational limitations of the exact methods. This advantage makes our asymptotic approach more practical for sample size computations at the planning stages of a large study. We illustrate the method with data arising from both proportional and non-proportional odds models in the two ordered multinomial setting.
Subject(s)
Biometry/methods , Sample Size , Linear Models , Models, Statistical , Research Design/statistics & numerical data , United StatesABSTRACT
OBJECTIVE: To identify and quantify the craniofacial effects from prenatal exposure to phenytoin monotherapy and polytherapy using cephalometric, hand-wrist, and panoramic radiographs and to determine if such deviations persist with age. DESIGN: Craniofacial structures of 28 anticonvulsant-exposed individuals were evaluated using 20 landmarks in lateral cephalometric radiographs and 19 landmarks in frontal cephalometric radiographs. Skeletal maturity was assessed using hand-wrist radiographs. Dental maturity and the presence of dental anomalies were evaluated using panoramic radiographs. Eleven individuals were re-evaluated 7 years later, on average, to determine the persistence of any measured deviations. SETTING AND SAMPLE POPULATION: Department of Growth and Development, Harvard School of Dental Medicine and Massachusetts General Hospital. Patients were recruited from several sources. OUTCOME MEASURE: The evaluated dimensions included linear, angular, and proportional measures. RESULTS: The most common deviations were decreased height and length of the maxilla, decreased length of the posterior cranial base, length of the mandible, cranial width and level of the cribriform plate, and a decrease in the Wits Appraisal assessment. The deviations were more significant in the polytherapy-exposed individuals than in the monotherapyexposed individuals. These deviations, especially in the maxilla, persisted with age as revealed in a re-evaluation of 11 individuals. CONCLUSION: The craniofacial skeletal findings among individuals exposed in utero to phenytoin monotherapy or phenytoin polytherapy, when considered in aggregate, suggest a mild pattern of maxillary hypoplasia that becomes more pronounced with age.
Subject(s)
Anticonvulsants/adverse effects , Facial Bones/drug effects , Phenytoin/adverse effects , Prenatal Exposure Delayed Effects , Skull/drug effects , Abnormalities, Drug-Induced/diagnostic imaging , Adolescent , Age Determination by Skeleton , Age Determination by Teeth , Cephalometry , Child , Drug Combinations , Ethmoid Bone/drug effects , Ethmoid Bone/pathology , Facial Bones/pathology , Female , Follow-Up Studies , Humans , Image Processing, Computer-Assisted , Male , Mandible/drug effects , Mandible/pathology , Maxilla/drug effects , Maxilla/pathology , Pregnancy , Radiography, Panoramic , Skull/pathology , Skull Base/drug effects , Skull Base/pathology , Statistics as Topic , Tooth Abnormalities/chemically induced , Tooth Abnormalities/diagnostic imagingABSTRACT
Often, the functional form of covariate effects in an additive model varies across groups defined by levels of a categorical variable. This structure represents a factor-by-curve interaction. This article presents penalized spline models that incorporate factor-by-curve interactions into additive models. A mixed model formulation for penalized splines allows for straightforward model fitting and smoothing parameter selection. We illustrate the proposed model by applying it to pollen ragweed data in which seasonal trends vary by year.
Subject(s)
Models, Statistical , Plant Proteins , Pollen , Biometry/methods , Cycadopsida , Michigan , Rain , SeasonsABSTRACT
BACKGROUND: The frequency of major malformations, growth retardation, and hypoplasia of the midface and fingers, known as the anticonvulsant embryopathy, is increased in infants exposed to anticonvulsant drugs in utero. However, whether the abnormalities are caused by the maternal epilepsy itself or by exposure to anticonvulsant drugs is not known. METHODS: We screened 128,049 pregnant women at delivery to identify three groups of infants: those exposed to anticonvulsant drugs, those unexposed to anticonvulsant drugs but with a maternal history of seizures, and those unexposed to anticonvulsant drugs with no maternal history of seizures (control group). The infants were examined systematically for the presence of major malformations, signs of hypoplasia of the midface and fingers, microcephaly, and small body size. RESULTS: The combined frequency of anticonvulsant embryopathy was higher in 223 infants exposed to one anticonvulsant drug than in 508 control infants (20.6 percent vs. 8.5 percent; odds ratio, 2.8; 95 percent confidence interval, 1.1 to 9.7). The frequency was also higher in 93 infants exposed to two or more anticonvulsant drugs than in the controls (28.0 percent vs. 8.5 percent; odds ratio, 4.2; 95 percent confidence interval, 1.1 to 5.1). The 98 infants whose mothers had a history of epilepsy but took no anticonvulsant drugs during the pregnancy did not have a higher frequency of those abnormalities than the control infants. CONCLUSIONS: A distinctive pattern of physical abnormalities in infants of mothers with epilepsy is associated with the use of anticonvulsant drugs during pregnancy, rather than with epilepsy itself.
Subject(s)
Abnormalities, Drug-Induced/etiology , Anticonvulsants/adverse effects , Epilepsy/drug therapy , Pregnancy Complications/drug therapy , Abnormalities, Drug-Induced/epidemiology , Carbamazepine/adverse effects , Case-Control Studies , Congenital Abnormalities/epidemiology , Congenital Abnormalities/etiology , Face/abnormalities , Female , Fetal Growth Retardation/chemically induced , Fingers/abnormalities , Humans , Infant, Newborn , Logistic Models , Phenobarbital/adverse effects , Phenytoin/adverse effects , Pregnancy , Valproic Acid/adverse effectsABSTRACT
We conduct a reanalysis of data from the Utah Valley respiratory health/air pollution study of Pope and co-workers (Pope et al., 1991) using additive mixed models. A relatively recent statistical development (e.g. Wang, 1998; Verbyla et al., 1999; Lin and Zhang, 1999), the methods allow for smooth functional relationships, subject-specific effects and time series error structure. All three of these are apparent in the Utah Valley data.
ABSTRACT
The multivariate binomial logit-normal distribution is a mixture distribution for which, (i) conditional on a set of success probabilities and sample size indices, a vector of counts is independent binomial variates, and (ii) the vector of logits of the parameters has a multivariate normal distribution. We use this distribution to model multivariate binomial-type responses using a vector of random effects. The vector of logits of parameters has a mean that is a linear function of explanatory variables and has an unspecified or partly specified covariance matrix. The model generalizes and provides greater flexibility than the univariate model that uses a normal random effect to account for positive correlations in clustered data. The multivariate model is useful when different elements of the response vector refer to different characteristics, each of which may naturally have its own random effect. It is also useful for repeated binary measurement of a single response when there is a nonexchangeable association structure, such as one often expects with longitudinal data or when negative association exists for at least one pair of responses. We apply the model to an influenza study with repeated responses in which some pairs are negatively associated and to a developmental toxicity study with continuation-ratio logits applied to an ordinal response with clustered observations.
Subject(s)
Models, Statistical , Abnormalities, Drug-Induced/etiology , Animals , Biometry , Epidemiologic Methods , Ethylene Glycol/administration & dosage , Ethylene Glycol/toxicity , Female , Humans , Influenza, Human/epidemiology , Linear Models , Logistic Models , Mice , Multivariate Analysis , PregnancyABSTRACT
We examine issues in estimating population size N with capture-recapture models when there is variable catchability among subjects. We focus on a logistic-normal mixed model, for which the logit of the probability of capture is an additive function of a random subject and a fixed sampling occasion parameter. When the probability of capture is small or the degree of heterogeneity is large, the log-likelihood surface is relatively flat and it is difficult to obtain much information about N. We also discuss a latent class model and a log-linear model that account for heterogeneity and show that the log-linear model has greater scope. Models assuming homogeneity provide much narrower intervals for N but are usually highly overly optimistic, the actual coverage probability being much lower than the nominal level.
Subject(s)
Biometry , Logistic Models , Animals , Lagomorpha , Linear Models , Models, Statistical , Population DensityABSTRACT
The data set presented relates a binomial response to ordered levels of an explanatory variable, representing doses of a drug, with data collected at several centers. A study goal is to test independence of the response and the ordinal factor, assuming under the alternative only that the binomial parameter is a monotonically increasing function of the ordinal predictor. We present two likelihood-ratio tests that are sensitive to order-restricted alternatives. Simulating the exact distributions of the test statistics yields nearly exact P-values. We also discuss related analyses for comparing two groups on an ordinal response, and we propose a test that is sensitive to a stochastic ordering alternative.