Precautionary principles: a jurisdiction-free framework for decision-making under risk

Science-policy in environmental and health risk assessment: if we cannot do without, can we do better?

How can empirical evidence of adverse effects from exposure to noxious agents, which is often incomplete and uncertain, be used most appropriately to protect human health? We examine several important questions on the best uses of empirical evidence in regulatory risk management decision–making raised by the US Environmental Protection Agency (EPA)'s science–policy concerning uncertainty and variability in human health risk assessment. In our view, the US EPA (and other agencies that have adopted similar views of risk management) can often improve decision–making by decreasing reliance on default values and assumptions, particularly when causation is uncertain. This can be achieved by more fully exploiting decision–theoretic methods and criteria that explicitly account for uncertain, possibly conflicting scientific beliefs and that can be fully studied by advocates and adversaries of a policy choice, in administrative decision–making involving risk assessment. The substitution of decision–theoretic frameworks for default assumption–driven policies also allows stakeholder attitudes toward risk to be incorporated into policy debates, so that the public and risk managers can more explicitly identify the roles of risk–aversion or other attitudes toward risk and uncertainty in policy recommendations. Decision theory provides a sound scientific way explicitly to account for new knowledge and its effects on eventual policy choices. Although these improvements can complicate regulatory analyses, simplifying default assumptions can create substantial costs to society and can prematurely cut off consideration of new scientific insights (e.g., possible beneficial health effects from exposure to sufficiently low ‘hormetic’ doses of some agents). In many cases, the administrative burden of applying decision–analytic methods is likely to be more than offset by improved effectiveness of regulations in achieving desired goals. Because many foreign jurisdictions adopt US EPA reasoning and methods of risk analysis, it may be especially valuable to incorporate decision–theoretic principles that transcend local differences among jurisdictions.

Worldwide withdrawal of medicinal products because of adverse drug reactions: a systematic review and analysis

We have systematically identified medicinal products withdrawn worldwide because of adverse drug reactions, assessed the level of evidence used for making the withdrawal decisions, and explored the patterns of withdrawals over time. We searched PubMed, the WHO database of withdrawn products, and selected texts. We included products that were withdrawn after launch from 1950 onwards, excluding non-human and over-the-counter medicines. We assessed the levels of evidence on which withdrawals were based using the Oxford Center for Evidence Based Medicine Levels of Evidence. Of 353 medicinal products withdrawn from any country, only 40 were withdrawn worldwide. Anecdotal reports were cited as evidence for withdrawal in 30 (75%) and deaths occurred in 27 (68%). Hepatic, cardiac, and nervous system toxicity accounted for over 60% of withdrawals. In 28 cases, the first withdrawal was initiated by the manufacturer. The median interval between the first report of an adverse drug reaction that led to withdrawal and the first withdrawal was 1 year (range 0-43 years). Worldwide withdrawals occurred within 1 year after the first withdrawal in any country. In conclusion, the time it takes for drugs to be withdrawn worldwide after reports of adverse drug reactions has shortened over time. However, there are inconsistencies in current withdrawal procedures when adverse drug reactions are suspected. A uniform method for establishing worldwide withdrawal of approved medicinal products when adverse drug reactions are suspected should be developed, to facilitate global withdrawals. Rapid synthesis of the evidence on harms should be a priority when serious adverse reactions are suspected.

Uncertainty in environmental health impact assessment: quantitative methods and perspectives

Environmental health impact assessment models are subjected to great uncertainty due to the complex associations between environmental exposures and health. Quantifying the impact of uncertainty is important if the models are used to support health policy decisions. We conducted a systematic review to identify and appraise current methods used to quantify the uncertainty in environmental health impact assessment. In the 19 studies meeting the inclusion criteria, several methods were identified. These were grouped into random sampling methods, second-order probability methods, Bayesian methods, fuzzy sets, and deterministic sensitivity analysis methods. All 19 studies addressed the uncertainty in the parameter values but only 5 of the studies also addressed the uncertainty in the structure of the models. None of the articles reviewed considered conceptual sources of uncertainty associated with the framing assumptions or the conceptualisation of the model. Future research should attempt to broaden the way uncertainty is taken into account in environmental health impact assessments.

Just who is at risk? The ethics of environmental regulation

The willingness to view risk as part of daily life has vanished. A risk-averse mindset among environmental regulators engenders confusion between the ethics of intention and the ethics of consequence, leading to the elevation of the precautionary principle with unintended and often unfortunate outcomes. Environmental risk assessment is conservative, but the actual level of conservatism cannot be determined. High-end exposure assumptions and current toxicity criteria from the USEPA, based on linear extrapolation for carcinogens and default uncertainty factors for systemic toxicants, obscure the degree of conservatism in risk assessments. Ideally, one could choose a percentile of the target population to include within environmental standards, but this choice is complicated by the food, pharmaceutical and advertising industries, whose activities, inadvertent or not, often promote maladaptive and unhealthy lifestyle choices. There has lately been much discussion about background exposures and disease processes and their potential to increase the risk from environmental chemicals. Should these background exposures or disease processes, especially those associated with maladaptive individual choices, be included as part of a regulatory risk evaluation? A significant ethical question is whether environmental regulation should protect those pursuing a self-destructive lifestyle that may add to or synergize with otherwise innocuous environmental exposures. Choosing a target percentile of protection would provide an increased level of transparency and the flexibility to choose a higher or lower percentile if such a choice is warranted. Transparency and flexibility will lead to more responsive environmental regulation that balances protection of public health and the stewardship of societal resources.

Causal regulations vs. political will: why human zoonotic infections increase despite precautionary bans on animal antibiotics

Using precautionary principles when facing incomplete facts and causal conjectures raises the possibility of a Faustian bargain. This paper applies systems dynamics based on previously unavailable data to show how well intended precautionary policies for promoting food safety may backfire unless they are informed by quantitative cause-and-effect models of how animal antibiotics affect animal and human health. We focus on European Union and United States formulations of regulatory precaution and then analyze zoonotic infections in terms of the consequences of relying on political will to justify precautionary bans. We do not attempt a political analysis of these issues; rather, we conduct a regulatory analysis of precautionary legal requirements and use Quantitative Risk Assessment (QRA) to assess a set of policy outcomes. Thirty-seven years ago, the Joint Committee on the Use of Antibiotics in Animal Husbandry and Veterinary Medicine (the Swann Report) warned that uncontrolled use of similar antibiotics in humans and food animals could promote the emergence of resistant strains of foodborne bacteria that could endanger human health. Since then, many countries have either banned or restricted antibiotics as feed additives for promoting animal growth. Others, including the United States, have relied on prudent use guidelines and programs that reduce total microbial loads, rather than focusing exclusively on antibiotic-resistant bacteria. In retrospect, the regulatory strategy of banning or restricting animal antibiotic uses has had limited success: it has been followed in many cases by deteriorating animal health and increases in human illnesses and resistance rates. Conversely, a combination of continued prudent use of antibiotics to prevent and control animal infections, together with HACCP and other improvements, has been followed by large improvements in the microbial safety of chickens and other food animals in the United States, leaving both animals and people better off now than they were decades ago. A quantitative risk assessment model of microbiological risks (Campylobacter because of data availability) suggests that these outcomes may be more than coincidental: prudent use of animal antibiotics may actually improve human health, while bans on animal antibiotics, intended to be precautionary, inadvertently may harm human health.

Hormesis and precaution: the twain shall meet

Regulatory focus on quantifying risk of disease or death from exposure to hazardous substances via monotonic dose-response models has downplayed or even rejected potential benefits to human health from exposures to low (sub-threshold) doses, and thus represented by either U-shaped or J-shaped models. On the other hand, most environmental health policy hypothesizes, without firm evidence, that cancer risk is proportional to exposure at low doses of current ambient exposures. An acceptable exposure is determined by either setting a somewhat arbitrary ;acceptable' level of risk, such as one in a million excess individual lifetime cancer risk or, in the case of several types of animal toxicological test results, applying multiplicative safety factors to a specific concentration, generally derived from a benchmark dose or NOAEL. This seemingly precautionary approach is questionable in light of much experimental evidence indicating protective effects of exposure at low doses - U-shaped or J-shaped models. We demonstrate that incorporating the possibility of hormesis into regulatory decision-making is precautionary, while use of default results in policy conflicts with precaution.

Regulation of endocrine-disrupting chemicals: critical overview and deficiencies in toxicology and risk assessment for human health

Regulation of endocrine-disrupting chemicals is reviewed in terms of hazard assessment (regulatory toxicology) and risk assessment. The current range of regulatory general toxicology protocols can detect endocrine toxicity, but specific endocrine toxicology tests are required to confirm mechanisms (e.g. oestrogenic, anti-androgenic). Strategies for validating new endocrine toxicology protocols and approaches to data assessment are discussed, and deficiencies in regulatory toxicology testing (e.g. lack of adrenocortical function assessment) identified. Recent evidence of a role of prolactin in human breast cancer also highlights deficiencies in regulatory evaluation. Actual human exposure to chemicals and the high-exposure example of chemicals in body-care cosmetics is reviewed with reference to evidence that common ingredients (e.g. parabens, cyclosiloxanes) are oestrogenic. The hypothesis and epidemiology concerning chemical exposure from body-care cosmetics (moisturizers, lotions, sun screens, deodorants) and breast cancer in women is reviewed, applying Bradford-Hill criteria for association and causality, and research requirements are identified.