Adjusting for bias due to incomplete case ascertainment in case-control studies of birth defects

Case-Control Study of Congenital Anomalies: Study Methods and Nonresponse Bias Assessment

BACKGROUND

To describe the methods of a congenital anomalies case-control study conducted in New Zealand, discuss the encountered methodological difficulties, and evaluate the potential for nonresponse bias.

METHODS

The potential cases (n = 2710) were New Zealand live births in 2007-2009 randomly selected from the New Zealand Congenital Anomalies Registry. The potential controls (n = 2989) included live births identified from the Maternity and Newborn Information System, frequency matched to cases by the child's year of birth and sex. Mothers were invited to complete an interview covering demographic, lifestyle, and environmental factors. Response probabilities for case and control mothers were evaluated in relation to maternal age, deprivation, occupation, and ethnicity, available from the Electoral Roll, and inverse probability weights (IPWs) for participation were calculated. Odds ratios (ORs) for key demographic and selected risk factors were estimated through unconditional logistic regression, with and without IPW.

RESULTS

A total of 652 (24%) of case mothers and 505 (17%) of control mothers completed the interview. Younger and more deprived mothers were underrepresented among the participants, particularly for controls, resulting in inflated ORs of associations with congenital anomalies for younger age, Māori ethnicity, deprivation, and risk factors under study, such as blue-collar occupations and smoking, indicative of nonresponse bias. Nonresponse bias was minimized through IPW, resulting in ORs and exposure prevalence estimates similar to those based on the prerecruitment sample.

CONCLUSIONS

Attaining high participation rates was difficult in this study that was conducted in new mothers, particularly for the controls. The resulting nonresponse bias was minimized through IPW.

Evaluation of quantitative bias analysis in epidemiological research: A systematic review from 2010 to mid-2023

OBJECTIVE

We aimed to demonstrate the use of quantitative bias analysis (QBA), which reveals the effects of systematic error, including confounding, misclassification and selection bias, on study results in epidemiological studies published in the period from 2010 to mid-23.

METHOD

The articles identified through a keyword search using Pubmed and Scopus were included in the study. The articles obtained from this search were eliminated according to the exclusion criteria, and the articles in which QBA analysis was applied were included in the detailed evaluation.

RESULTS

It can be said that the application of QBA analysis has gradually increased over the 13-year period. Accordingly, the number of articles in which simple is used as a method in QBA analysis is 9 (9.89%), the number of articles in which the multidimensional approach is used is 10 (10.99%), the number of articles in which the probabilistic approach is used is 60 (65.93%) and the number of articles in which the method is not specified is 12 (13.19%). The number of articles with misclassification bias model is 44 (48.35%), the number of articles with uncontrolled confounder(s) bias model is 32 (35.16%), the number of articles with selection bias model is 7 (7.69%) and the number of articles using more than one bias model is 8 (8.79%). Of the 49 (53.85%) articles in which the bias parameter source was specified, 19 (38.78%) used internal validation, 26 (53.06%) used external validation and 4 (8.16%) used educated guess, data constraints and hypothetical data. Probabilistic approach was used as a bias method in 60 (65.93%) of the articles, and mostly beta (8 [13.33%)], normal (9 [15.00%]) and uniform (8 [13.33%]) distributions were selected.

CONCLUSION

The application of QBA is rare in the literature but is increasing over time. Future researchers should include detailed analyzes such as QBA analysis to obtain inferences with higher evidence value, taking into account systematic errors.

Bias analyses to investigate the impact of differential participation: Application to a birth defects case-control study

BACKGROUND

Certain associations observed in the National Birth Defects Prevention Study (NBDPS) contrasted with other research or were from areas with mixed findings, including no decrease in odds of spina bifida with periconceptional folic acid supplementation, moderately increased cleft palate odds with ondansetron use and reduced hypospadias odds with maternal smoking.

OBJECTIVES

To investigate the plausibility and extent of differential participation to produce effect estimates observed in NBDPS.

METHODS

We searched the literature for factors related to these exposures and participation and conducted deterministic quantitative bias analyses. We estimated case-control participation and expected exposure prevalence based on internal and external reports, respectively. For the folic acid-spina bifida and ondansetron-cleft palate analyses, we hypothesized the true odds ratio (OR) based on prior studies and quantified the degree of exposure over- (or under-) representation to produce the crude OR (cOR) in NBDPS. For the smoking-hypospadias analysis, we estimated the extent of selection bias needed to nullify the association as well as the maximum potential harmful OR.

RESULTS

Under our assumptions (participation, exposure prevalence, true OR), there was overrepresentation of folic acid use and underrepresentation of ondansetron use and smoking among participants. Folic acid-exposed spina bifida cases would need to have been ≥1.2× more likely to participate than exposed controls to yield the observed null cOR. Ondansetron-exposed cleft palate cases would need to have been 1.6× more likely to participate than exposed controls if the true OR is null. Smoking-exposed hypospadias cases would need to have been ≥1.2 times less likely to participate than exposed controls for the association to falsely appear protective (upper bound of selection bias adjusted smoking-hypospadias OR = 2.02).

CONCLUSIONS

Differential participation could partly explain certain associations observed in NBDPS, but questions remain about why. Potential impacts of other systematic errors (e.g. exposure misclassification) could be informed by additional research.

Prenatal exposure to wildfire-related air pollution and birth defects in Brazil

BACKGROUND

Birth defects are a major cause of poor health outcomes during both childhood and adulthood. A growing body of evidence demonstrated associations between air pollution exposure during pregnancy and birth defects. To date, there is no study looking at birth defects and exposure to wildfire-related air pollution, which is suggested as a type of air pollution source with high toxicity for reproductive health.

OBJECTIVE

Our study addresses this gap by examining the association between birth defects and wildfire smoke exposure in Brazil between 2001 and 2018. Based on known differences of impacts of wildfires across different regions of Brazil, we hypothesized differences in risks of birth defects for different regions.

METHODS

We used a logistic regression model to estimate the odds ratios (ORs) for individual birth defects (12 categories) associated with wildfire exposure during each trimester of pregnancy.

RESULTS

Among the 16,825,497 birth records in our study population, there were a total of 7595 infants born in Brazil between 2001 and 2018 with birth defects in any of the selected categories. After adjusting for several confounders in the primary analysis, we found statistically significant OR for three birth defects, including cleft lip/cleft palate [OR: 1.007 (95% CI: 1.001; 1.013)] during the second trimester of exposure, congenital anomalies of the respiratory system [OR: 1.013 (95% CI: 1.002; 1.023)] in the second trimester of exposure, and congenital anomalies of the nervous system [OR: 1.002 (95% CI: 1.001; 1.003)] during the first trimester of exposure for the regions South, North, and Midwest, respectively.

SIGNIFICANCE

Our results suggest that maternal exposure to wildfire smoke during pregnancy may increase the risk of an infant being born with some congenital anomaly. Considering that birth defects are associated with long-term disability, impacting families and the healthcare system (e.g., healthcare costs), our findings should be of great concern to the public health community.

IMPACT STATEMENT

Our study focused on the association between maternal exposure to wildfire smoke in Brazil during pregnancy and the risk of an infant being born with congenital anomalies, which presents serious public health and environmental challenges.

Quantifying the influence of bias in reproductive and perinatal epidemiology through simulation

PURPOSE

The application of simulated data in epidemiological studies enables the illustration and quantification of the magnitude of various types of bias commonly found in observational studies. This was a review of the application of simulation methods to the quantification of bias in reproductive and perinatal epidemiology and an assessment of value gained.

METHODS

A search of published studies available in English was conducted in August 2020 using PubMed, Medline, Embase, CINAHL, and Scopus. A gray literature search of Google and Google Scholar, and a hand search using the reference lists of included studies was undertaken.

RESULTS

Thirty-nine papers were included in this study, covering information (n = 14), selection (n = 14), confounding (n = 9), protection (n = 1), and attenuation bias (n = 1). The methods of simulating data and reporting of results varied, with more recent studies including causal diagrams. Few studies included code for replication.

CONCLUSIONS

Although there has been an increasing application of simulation in reproductive and perinatal epidemiology since 2015, overall this remains an underexplored area. Further efforts are required to increase knowledge of how the application of simulation can quantify the influence of bias, including improved design, analysis and reporting. This will improve causal interpretation in reproductive and perinatal studies.

A systematic review of quantitative bias analysis applied to epidemiological research

BACKGROUND

Quantitative bias analysis (QBA) measures study errors in terms of direction, magnitude and uncertainty. This systematic review aimed to describe how QBA has been applied in epidemiological research in 2006-19.

METHODS

We searched PubMed for English peer-reviewed studies applying QBA to real-data applications. We also included studies citing selected sources or which were identified in a previous QBA review in pharmacoepidemiology. For each study, we extracted the rationale, methodology, bias-adjusted results and interpretation and assessed factors associated with reproducibility.

RESULTS

Of the 238 studies, the majority were embedded within papers whose main inferences were drawn from conventional approaches as secondary (sensitivity) analyses to quantity-specific biases (52%) or to assess the extent of bias required to shift the point estimate to the null (25%); 10% were standalone papers. The most common approach was probabilistic (57%). Misclassification was modelled in 57%, uncontrolled confounder(s) in 40% and selection bias in 17%. Most did not consider multiple biases or correlations between errors. When specified, bias parameters came from the literature (48%) more often than internal validation studies (29%). The majority (60%) of analyses resulted in >10% change from the conventional point estimate; however, most investigators (63%) did not alter their original interpretation. Degree of reproducibility related to inclusion of code, formulas, sensitivity analyses and supplementary materials, as well as the QBA rationale.

CONCLUSIONS

QBA applications were rare though increased over time. Future investigators should reference good practices and include details to promote transparency and to serve as a reference for other researchers.

Original article: is the protective association between hyperemesis gravidarum and birth defects biased by pregnancy termination?

PURPOSE

We assessed whether the protective association between hyperemesis gravidarum and birth defects could be due to selection bias from exclusion of pregnancy terminations.

METHODS

We designed a cohort study of 2,115,581 live births in Canada, 1990-2016. The main exposure measure was hyperemesis gravidarum. The main outcome measure included any birth defect at delivery. We estimated risk ratios (RR) and 95% confidence intervals (CI) for the association of hyperemesis gravidarum with birth defects in log-binomial regression models, and assessed the extent of selection bias through correction factors.

RESULTS

Hyperemesis gravidarum was associated with 0.88 times the risk of birth defects in models not corrected for bias (95% CI 0.82-0.94). Correction for selection bias suggested that if screening for birth defects was associated with 1.33 times the chance of detecting birth defects and having a pregnancy termination, there would be no association with hyperemesis gravidarum. If ultrasound was associated with 2.00 times the chance of detecting birth defects and 1.50 times the risk of pregnancy termination, hyperemesis gravidarum would be associated with 1.27 times the risk of birth defects (95% CI 1.18-1.35).

CONCLUSIONS

The protective association between hyperemesis gravidarum and birth defects in previous studies may be due to selection bias.

Educational note: addressing special cases of bias that frequently occur in perinatal epidemiology

The epidemiologic study of pregnancy and birth outcomes may be hindered by several unique and challenging issues. Pregnancy is a time-limited period in which severe cohort attrition takes place between conception and birth and adverse outcomes are complex and multi-factorial. Biases span those familiar to epidemiologists: selection, confounding and information biases. Specific challenges include conditioning on potential intermediates, how to treat race/ethnicity, and influential windows of prolonged, seasonal and potentially time-varying exposures. Researchers studying perinatal outcomes should be cognizant of the potential pitfalls due to these factors and address their implications with respect to formulating questions of interest, choice of an appropriate analysis approach and interpretations of findings given assumptions. In this article, we catalogue some of the more important potential sources of bias in perinatal epidemiology that have more recently gained attention in the literature, provide the epidemiologic context behind each issue and propose practices for dealing with each issue to the extent possible.

Prepregnancy body mass index and spina bifida: Potential contributions of bias

BACKGROUND

Epidemiologists have consistently observed associations between prepregnancy obesity and spina bifida in offspring. Most studies, however, used self-reported body mass index (potential for exposure misclassification) and incompletely ascertained cases of spina bifida among terminations of pregnancy (potential for selection bias). We conducted a quantitative bias analysis to explore the potential effects of these biases on study results.

METHODS

We included 808 mothers of fetuses or infants with spina bifida (case mothers) and 7,685 mothers of infants without birth defects (control mothers) from a population-based case-control study, the National Birth Defects Prevention Study (1997-2011). First, we performed a conventional epidemiologic analysis, adjusting for potential confounders using logistic regression. Then, we used 5,000 iterations of probabilistic bias analysis to adjust for the combination of confounding, exposure misclassification, and selection bias.

RESULTS

In the conventional confounding-adjusted analysis, prepregnancy obesity was associated with spina bifida (odds ratio 1.4, 95% confidence interval: 1.2, 1.7). In the probabilistic bias analysis, we tested nine different models for the combined effects of confounding, exposure misclassification, and selection bias. Results were consistent with a weak to moderate association between prepregnancy obesity and spina bifida, with the median odds ratios across the nine models ranging from 1.1 to 1.4.

CONCLUSIONS

Given our assumptions about the occurrence of bias in the study, our results suggest that exposure misclassification, selection bias, and confounding do not completely explain the association between prepregnancy obesity and spina bifida.

Association of maternal food insecurity before and during pregnancy with fetal structural anomalies: A multicenter case-control study protocol

BACKGROUND

Food insecurity, an issue also affecting developed countries, is associated with different negative outcomes. Particularly in pregnant women, a vulnerable population group, it has a double burden, as it affects both the woman and her child. Food insecurity has been associated with low birth weight and shorter gestational age, but there is less evidence on the association with fetal structural anomalies.

AIM

To fill this gap, a study will be conducted to examine if pregnant women in a condition of food insecurity have a higher risk for fetal structural anomalies.

METHODS

A case-control study will be conducted in three centers. Cases will be pregnant women (>18 years old) diagnosed with a fetal structural anomaly during the prenatal ultrasound examination of the II-III trimester, while controls will be pregnant women (>18 years old) with a negative result for fetal structural anomaly at the II-III trimester prenatal ultrasound examination. The exposure of interest will be food insecurity during the last 12 months, measured using the validated Household Food Insecurity Access Scale. A dedicated questionnaire will be given to women after they sign the informed consent form.

SUMMARY

Finding a positive association between food insecurity in pregnant women and fetal structural anomalies could be the first step towards screening for it among pregnant women and designing policies that could mitigate this condition. Lowering food insecurity could prevent a certain number of fetal structural anomalies, leading to fewer negative pregnancy outcomes and health problems during childhood and adulthood.

Quantification of selection bias in studies of risk factors for birth defects among livebirths

BACKGROUND

Risk factors for birth defects are frequently investigated using data limited to liveborn infants. By conditioning on survival, results of such studies may be distorted by selection bias, also described as "livebirth bias." However, the implications of livebirth bias on risk estimation remain poorly understood.

OBJECTIVES

We sought to quantify livebirth bias and to investigate the conditions under which it arose.

METHODS

We used data on 3994 birth defects cases and 11 829 controls enrolled in the National Birth Defects Prevention Study to compare odds ratio (OR) estimates of the relationship between three established risk factors (antiepileptic drug use, smoking, and multifetal pregnancy) and four birth defects (anencephaly, spina bifida, omphalocele, and cleft palate) when restricted to livebirths as compared to among livebirths, stillbirths, and elective terminations. Exposures and birth defects represented varying strengths of association with livebirth; all controls were liveborn. We performed a quantitative bias analysis to evaluate the sensitivity of our results to excluding terminated and stillborn controls.

RESULTS

Cases ranged from 33% liveborn (anencephaly) to 99% (cleft palate). Smoking and multifetal pregnancy were associated with livebirth among anencephaly (crude OR [cOR] 0.61 and cOR 3.15, respectively) and omphalocele cases (cOR 2.22 and cOR 5.22, respectively). For analyses of the association between exposures and birth defects, restricting to livebirths produced negligible differences in estimates except for anencephaly and multifetal pregnancy, which was twofold higher among livebirths (adjusted OR [aOR] 4.93) as among all pregnancy outcomes (aOR 2.44). Within tested scenarios, bias analyses suggested that results were not sensitive to the restriction to liveborn controls.

CONCLUSIONS

Selection bias was generally limited except for high mortality defects in the context of exposures strongly associated with livebirth. Findings indicate that substantial livebirth bias is unlikely to affect studies of risk factors for most birth defects.

Association between maternal pregestational diabetes mellitus and spina bifida: A population-based case-control study, Finland, 2000-2014

BACKGROUND

Maternal pregestational diabetes mellitus (PGDM) is a known risk factor for neural tube defects. We examined the association between maternal PGDM and spina bifida in the offspring using PGDM status from medical records in Finland.

METHODS

We conducted a nationally representative, multiregistry, population-based case-control study in Finland. Cases were included if they were live or stillborn infants and diagnosed with spina bifida and delivered between years 2000 and 2014 in Finland. Controls were Finnish infants without spina bifida or other major structural birth defects and delivered during the same time period as cases. Clinical and demographic data were obtained by linking multiple national health registers and census. Crude and adjusted odds ratios (ORs) and 95% confidence intervals (CI) for PGDM were estimated using logistic regression analysis. Interaction by maternal obesity was examined.

RESULTS

Our study included 181 spina bifida cases (61% isolated) and 876,672 controls. Overall, 2.2% percent of all case, and 0.5% of control mothers, had PGDM during pregnancy. Maternal PGDM was significantly associated with an increased odds of spina bifida (adjusted OR 4.35; 95% CI 1.37, 13.82). A similar association was found in our subanalysis on isolated spina bifida cases (adjusted OR 4.41; 95% CI 1.07, 18.24). There was no significant interaction by maternal obesity.

CONCLUSIONS

Maternal PGDM was positively associated with spina bifida in Finland, and maternal obesity did not modify this effect. We lacked information on maternal PGDM for electively terminated and spontaneously aborted cases; results should be interpreted with caution.

Survival of infants with spina bifida and the role of maternal prepregnancy body mass index

OBJECTIVE

To investigate first-year survival of infants born with spina bifida, and examine the association of maternal prepregnancy body mass index (BMI) with infant mortality.

METHODS

This is a retrospective cohort study of 1,533 liveborn infants with nonsyndromic spina bifida with estimated dates of delivery from 1998 to 2011 whose mothers were eligible for the National Birth Defects Prevention Study (NBDPS). NBDPS data were linked to death records to conduct survival analyses. Kaplan-Meier survival functions estimated mortality risk over the first year of life. Cox proportional hazards models estimated hazard ratios (HRs) for maternal prepregnancy BMI categorized as underweight (<18.5), normal (18.5-24.9), overweight (25-29.9), and obese (≥30).

RESULTS

Infant mortality risk among infants with spina bifida was (4.4% [3.52, 5.60%]). Infants with multiple co-occurring defects, very preterm delivery, multiple gestation, high-level spina bifida lesions, or non-Hispanic Black mothers had an elevated risk of infant mortality. Maternal prepregnancy underweight and obesity were associated with higher infant mortality (15.7% [7.20, 32.30%] and 5.82% [3.60, 9.35%], respectively). Adjusted HR estimates showed underweight and obese mothers had greater hazard of infant mortality compared to normal weight mothers (HR: 4.5 [1.08, 16.72] and 2.6 [1.36, 8.02], respectively).

CONCLUSION

The overall risk of infant mortality for infants born with spina bifida was lower than most previously reported estimates. Infants born with spina bifida to mothers who were underweight or obese prepregnancy were at higher risk of infant mortality. This study provides additional evidence of the importance of healthy maternal weight prior to pregnancy.

Paternal and joint parental occupational pesticide exposure and spina bifida in the National Birth Defects Prevention Study, 1997 to 2002

BACKGROUND

Because of persistent concerns over the association between pesticides and spina bifida, we examined the role of paternal and combined parental occupational pesticide exposures in spina bifida in offspring using data from a large population-based study of birth defects.

METHODS

Occupational information from fathers of 291 spina bifida cases and 2745 unaffected live born control infants with estimated dates of delivery from 1997 to 2002 were collected by means of maternal report. Two expert industrial hygienists estimated exposure intensity and frequency to insecticides, herbicides, and fungicides. Multivariable logistic regression models were used to estimate adjusted odds ratios (aOR) and 95% confidence intervals (CI) for exposure to any pesticide and to any class of pesticide (yes/no; and by median), and exposure to combinations of pesticides (yes/no) and risk of spina bifida. Adjusted odds ratios were also estimated by parent exposed to pesticides (neither, mother only, father only, both parents).

RESULTS

Joint parental occupational pesticide exposure was positively associated with spina bifida (aOR, 1.5; 95% CI, 0.9-2.4) when compared with infants with neither maternal nor paternal exposures; a similar association was not observed when only one parent was exposed. There was a suggested positive association between combined paternal insecticide and fungicide exposures and spina bifida (aOR, 1.5; 95% CI, 0.8-2.8), however, nearly all other aORs were close to unity.

CONCLUSION

Overall, there was little evidence paternal occupational pesticide exposure was associated with spina bifida. However, the small numbers make it difficult to precisely evaluate the role of pesticide classes, individually and in combination. Birth Defects Research (Part A) 106:963-971, 2016. © 2016 Wiley Periodicals, Inc.

The Prevalence and Distribution of Spina Bifida in a Single Major Referral Center in Malaysia

BACKGROUND

The aim of this study is to review the medical history of patients with spina bifida, encompassing both aperta and occulta types born between the years 2003 until 2016, spanning a 13-year time period. We assessed each patient and maternal parent information, details of the defects, and conditions associated with the primary defect. We also include information on patients' ambulation and education level (where available).

METHODS

Data from the Department of Patient Information University of Malaya Medical Centre (UMMC), Malaysia was captured from spina bifida patients (ICD10: Q05 spina bifida). Data involved patients referred to UMMC between 2003 and 2016 and/or born in UMMC within that particular time frame. We filtered and extracted the information according to the data of clinical examination, medical review, and social history provided in the medical records.

RESULTS

A total of 86 patient records with spina bifida were analyzed. Spina bifida prevalence rate in this study ranged from 1.87 to 8.9 per 1,000 live births depending on weightage. We note that ethnicity was a factor whereby the highest numbers of spina bifida were from Malays (n = 36, 41.86%), followed by equal numbers of Chinese and Indians (n = 24, 27.91%). The highest number of diagnoses reported was myelomeningocele type-spina bifida (n = 39, 45.35%). The most common site of the spina bifida lesion was located at the lumbar region irrespective of aperta or occulta types (n = 23, 26.74%). Data on other associated phenotypes of spina bifida such as hydrocephalus and encephalocele was also captured at 37.21% (n = 32) and 1.16% (n = 1), respectively. In terms of mobility, 32.84% (n = 22/67) of patients between the ages 4 and 16 years old were found to be mobile. As many as 36.07% of patients ranging from 5 to 16 years of age (n = 22/61) received formal education ranging from preschool to secondary school.

CONCLUSION

The prevalence of spina bifida in UMMC is as according to international statistics which is in the range of 0.5-10 per 1,000 live births. Majority of the reported cases were males, Malays, full term babies, and of the myelomeningocele phenotype located at the lumbar region.

Constructing Causal Diagrams for Common Perinatal Outcomes: Benefits, Limitations and Motivating Examples with Maternal Antidepressant Use in Pregnancy

BACKGROUND

Covariate selection to reduce bias in observational data analysis has primarily relied upon statistical criteria to guide researchers. This approach may lead researchers to condition on variables that ultimately increase bias in the effect estimates. The use of directed acyclic graphs (DAGs) aids researchers in constructing thoughtful models based on hypothesised biologic mechanisms to produce the least biased effect estimates possible.

METHODS

After providing an overview of different relations in DAGs and the prevailing mechanisms by which conditioning on variables increases or reduces bias in a model, we illustrate examples of DAGs for maternal antidepressants in pregnancy and four separate perinatal outcomes.

RESULTS

By comparing and contrasting the diagrams for maternal antidepressant use in pregnancy and spontaneous abortion, major malformations, preterm birth, and postnatal growth, we illustrate the different conditioning sets required for each model. Moreover, we illustrate why it is not appropriate to condition on the same set of covariates for the same exposure and different perinatal outcomes. We further discuss potential selection biases, overadjustment of mediators on the causal path, and sufficient sets of conditioning variables.

CONCLUSION

In our efforts to construct parsimonious models that minimise confounding and selection biases, we must rely upon our scientific knowledge of the causal mechanism. By structuring data collection and analysis around hypothesised DAGs, we ultimately aim to validly estimate the causal effect of interest.

Preventing birth defects: The value of the NBDPS case-control approach

Birth Defect Registries provide a basis for epidemiological research into risk factors, thus facilitating a growing understanding of what causes congenital anomalies and how one might target preventive public health actions and reduce inequalities. The National Birth Defects Prevention Study (NBDPS) has used 10 U.S. registries as a basis for a large case-control study. This commentary reviews its methodology and selected areas of output. The strengths of NBDPS lie in the quality of diagnostic coding and classification of birth defects and its size. The sources of bias in NBDPS data relate particularly to retrospective exposure ascertainment entailing a long period of recall, incomplete ascertainment of terminations of pregnancy for fetal anomaly, and unknown bias in case selection. NBDPS results have shown the protective effect of healthy dietary patterns, but have not been as informative as expected in relation to furthering understanding of the protective effect of folic acid. NBDPS medication studies are making important contributions to addressing the gap in existing evidence systematically across a wide range of birth defects, but are challenged by the quality of information on exposure, dose and underlying disease condition, and the interpretation of results of multiple testing. Studies of environmental contaminants in collaboration with experts in exposure assessment have linked addresses to residential exposure measures, using the advantages of information on residential history and confounders, but are challenged by the need to consider exposure mixtures. NBDPS could increase its public health impact by placing more emphasis on socioeconomic inequalities.