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Investigators from the Baltimore-Washington Infant Study (BWIS) reported an association between self-reported maternal lead exposure and total anomalous pulmonary venous return (TAPVR) in their offspring. This association was further evaluated in the BWIS population using a more sensitive exposure estimate.Cases included 54 live-born infants with TAPVR; controls were a stratified random sample of 522 live-born infants from the BWIS control group. Parental lead exposure was based on three assessment methods, including: an industrial hygiene assessment, an a priori job exposure matrix, and self-reported exposures. A parent was classified as exposed to lead if he/she was classified as exposed by any one of the assessment methods.Approximately 17% of case mothers and 11% of control mothers were classified as exposed to lead during the three months prior to conception through the first trimester (odds ratio [OR], 1.57; 95% confidence interval [CI], 0.64-3.47). Among fathers, 61% of case fathers and 46% of control fathers were classified as exposed to lead during the six months prior to conception (paternal critical period) (OR, 1.83; 95% CI, 1.00-3.42). During the paternal critical period, when only the father was exposed compared to neither parent exposed, the OR for any lead exposure and TAPVR was 1.65 (95% CI, 0.84-3.25).This study supports a possible association between paternal lead exposure and TAPVR. Further studies are warranted using validated assessment methods for occupational and nonoccupational lead exposures to corroborate this association and to elucidate the possible biological mechanism. Birth Defects Research (Part A), 2004.

Weak associations will be increasingly more important in epidemiology as we try to sort out the etiologic pathways of common but multifactorial diseases. The strong risk factors for disease such as smoking or asbestos and lung cancer have been identified through epidemiology and these situations may be less common in the future. This does not mean that some exposures today may not be causing high risks in the population. These factors are yet to be recognised. However, the usual situation is that epidemiology will be challenged to help the clinicians sort out the risk factors for common diseases where multiple etiologies and multiple steps in the pathway to disease exist. Each factor will then demonstrate only a low risk associated with disease. The challenge will be to determine whether these associations are real. Such data may always be subject to the interpretation of the individual investigator. However, it would be helpful to establish some guidelines that will minimise the chances of identifying inappropriate or false associations and clarifying the true associations. Currently, a weak association is often followed by studies which gather similar information on bigger populations or by doing meta-analysis on multiple populations. These procedures could simply root an incorrect observation in the trappings of validity by making it statistically significant. The observation may still be the result of inadequate attention to the possible confounding variables that are associated with the disease.

At present, exposure databases record data primarily for regulatory purposes; they have not focused on serving the needs of epidemiologists or public health. However, the modification of exposure databases could facilitate their use in epidemiology. Characteristics necessary to enhance the use of all databases include easy access by users; documentation of methods, sampling bias, error, and inconsistences; widespread coverage in time and space; and methods and measures for estimating exposure of individuals as well as populations. Also needed are exposure scenarios and models to estimate exposures for geographic areas and time intervals not currently sampled. Multidisciplinary teams are needed to examine current databases, to review strategies for improving data collection, and to suggest and help implement appropriate changes. A long-term goal is to develop and validate data from exposure scenarios and models using data on the relationship of exposure to doses measured in humans.