Biomedical subjects

C F Corvalán

Publications and source records attributed to C F Corvalán.

5 recordsLinked to original sources

PubMed1999

How much global ill health is attributable to environmental factors?

Over the years, estimates have been made of the portions of human mortality and morbidity that can be attributed to environmental factors. Frustratingly, however, even for a single category of disease such as cancer, these estimates have often varied widely. Here we attempt to explain why such efforts have come to such different results in the past and to provide guidance for doing such estimates more consistently in the future to avoid the most important pitfalls. We do so by carefully defining what we mean by the terms "environmental," "ill health," and "attributable." Finally, based on these recommendations, we attempt our own estimate, appropriately qualified according to the many remaining uncertainties. Our estimate is that 25-33% of the global burden of disease can be attributed to environmental risk factors. Children under 5 years of age seem to bear the largest environmental burden, and the portion of disease due to environmental risks seems to decrease with economic development. A summary of these estimates first appeared in the 1997 report, "Health and Environment in Sustainable Development," which was the World Health Organization's contribution to the 5-year anniversary of the Rio Earth Summit. A full explanation of how these estimates were made is first presented here. We end with a call for a program of "strategic epidemiology," which would be designed to fill important gaps in the understanding of major environmental health risks in important population groups worldwide.

Causality↗

PubMed1999

Methodologic issues in epidemiologic risk assessment.

This paper reviews methodologic issues pertinent to the application of epidemiology in risk assessment and discusses concerns in the presentation of results from such an activity. Assessment of the health risks associated with occupational and environmental exposures involves four phases: hazard identification, i.e., the detection of the potential for agents to cause adverse health effects in exposed populations; exposure assessment, i.e., the quantification of exposures and the estimation of the characteristics and sizes of the exposed populations; dose-response assessment, i.e., the modeling for risk realization; and risk characterization, i.e., the evaluation of the impact of a change in exposure levels on public health effects. The risk-assessment process involves limitations of exposure data, many assumptions, and subjective choices that need to be considered when using this approach to provide guidance for health policy or action. In view of these uncertainties, we suggest that the provision of estimates of individual risk and disease burden in a population must be accompanied by the corresponding estimates of precision; risks should be presented in a sufficiently disaggregated form so that population heterogeneities are not lost in the data aggregation; and different scenarios and risk models should be applied. The methods are illustrated by an assessment on the health impacts of exposure to silica.

Decision Support Techniques↗

PubMed1999

Health, environment and sustainable development: identifying links and indicators to promote action.

This paper discusses the links among health, environment, and sustainable development and presents a framework that extends from the epidemiological domain to the policy domain and includes the driving forces that generate environmental pressures, creating changes in the state of the environment and eventually contributing to human exposures. Health effects are the end result of this complex net of events. Environmental health interventions should not be limited to treatment of cases and directly reducing human exposures. The paper discusses the need for integrated action at all levels and, in particular, on the need to focus on long-term action directed at reducing the driving forces that generate the environmental health threats. Only this approach can achieve sustained health benefits and environmental protection in accord with the principles of sustainable development.

Decision Support Techniques↗

PubMed1991

The incidence of malignant mesothelioma in Australia 1982-1988.

From 1980 to 1985, the Australian Mesothelioma Surveillance Program, and since 1986, the Australian Mesothelioma Register, have been collecting data on all cases of malignant mesothelioma that could be ascertained in Australia. Incidence rates were calculated on 854 Program and 696 Register cases (total 1271) diagnosed in Australia between January 1, 1982 and December 31, 1988. Australia has one of the highest national rates of mesothelioma in the world (15.8 cases per million of population aged 20 years and older), and the rate is rising. The rate is far higher in males (28.3) than females (3.3). The Western Australian rate (28.9) is the highest among the states, as may be expected because of the crocidolite mine at Wittenoom; however, the largest numbers of cases occur in the more populous and industrial New South Wales. The high incidence rate, its expected continuing increase, and absence of a history of exposure to asbestos in approximately 28% of cases, demand consideration of potential environmental factors other than asbestos in the causation of this tumor, as well as continued surveillance.

Adult↗

PubMedDate not supplied

Methodologic considerations in estimating burden of disease from environmental risk factors at national and global levels.

Evidence from environmental burden-of-disease studies can provide valuable input in the decision-making process in environmental health, facilitating priority setting and cost effectiveness evaluation. This paper discusses important aspects of environmental burden-of-disease estimates in the light of) published examples. To produce reliable and comparable burden-of-disease estimates for environmental and occupational risk factors, harmonized methods are needed. Such methods should address the feasibility of data collection at national, regional, and global levels, the reliability of estimates, the uncertainty around estimates, and scenario tools to investigate the health gains of options for preventive action in different domains of policy. Any such method will require a framework (i.e., causal inference model) able to take into account the contributions of distal and proximal causes, and the possible interactions between risk factors.

Environmental Illness↗