Detailed descriptions of the magnitude and distribution of
diseases and injuries, and their causes are important
inputs to strategies for improving population health.
Much work has focused on the quantification of mortality
patterns and, more recently, on burden of disease.1,2 Data
on disease or injury outcomes alone, such as death or
admission to hospital, tend to focus on the need for
palliative or curative services. Reliable and comparable
analysis of risks to health, however, is key for preventing
disease and injury. Analysis of morbidity and mortality
due to risk factors has frequently been done in the context
of methodological traditions of individual risk factors and
in a limited number of settings.3–10 As a result, most such
estimates have been made relative to an arbitrary,
constant level of population exposure, without standardisation
of the baseline exposure across risk factors. For
example, the implicit baseline for much of the estimates of
occupational disease and injuries has been “no work”.
Furthermore, the criteria for assessment of scientific
evidence on prevalence, causality, and hazard size have
varied greatly across risk factors, resulting in lack of
comparability of estimated population health effects.
Finally, the outcome of such estimates has been morbidity
or mortality due to specific disease(s), making comparison
among different risk factors difficult.
Detailed descriptions of the magnitude and distribution of
diseases and injuries, and their causes are important
inputs to strategies for improving population health.
Much work has focused on the quantification of mortality
patterns and, more recently, on burden of disease.1,2 Data
on disease or injury outcomes alone, such as death or
admission to hospital, tend to focus on the need for
palliative or curative services. Reliable and comparable
analysis of risks to health, however, is key for preventing
disease and injury. Analysis of morbidity and mortality
due to risk factors has frequently been done in the context
of methodological traditions of individual risk factors and
in a limited number of settings.3–10 As a result, most such
estimates have been made relative to an arbitrary,
constant level of population exposure, without standardisation
of the baseline exposure across risk factors. For
example, the implicit baseline for much of the estimates of
occupational disease and injuries has been “no work”.
Furthermore, the criteria for assessment of scientific
evidence on prevalence, causality, and hazard size have
varied greatly across risk factors, resulting in lack of
comparability of estimated population health effects.
Finally, the outcome of such estimates has been morbidity
or mortality due to specific disease(s), making comparison
among different risk factors difficult.
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