Timely assessment of the aggregate health of small-area human populations is essential for guiding the optimal investment of resources needed for preventing, avoiding, controlling, or mitigating exposure risks. Seeking those interventions yielding the greatest benefit with respect to allocation of resources is essential for making progress toward community sustainability, promoting social justice, and maintaining or improving health and well-being. More efficient approaches are needed for revealing cause-effect linkages between environmental stressors and human health and for measuring overall aggregate health of small-area populations. A new concept is presented--community health assessment via Sewage Chemical Information Mining (SCIM)--for quickly gauging overall, aggregate health status or trends for entire small-area populations. The approach--BioSCIM--would monitor raw sewage for specific biomarkers broadly associated with human disease, stress, or health. A wealth of untapped chemical information resides in raw sewage, a portion comprising human biomarkers of exposure and effects. BioSCIM holds potential for capitalizing on the presence of biomarkers in sewage for accomplishing any number of objectives. One of the many potential applications of BioSCIM could use various biomarkers of stress resulting from the collective excretion from all individuals in a local population. A prototype example is presented using a class of biomarkers that measures collective, systemic oxidative stress--the isoprostanes (prostaglandin-like free-radical catalyzed oxidation products from certain polyunsaturated fatty acids). Sampling and analysis of raw sewage hold great potential for quickly determining aggregate biomarker levels for entire communities. Presented are the basic principles of BioSCIM, together with its anticipated limitations, challenges, and potential applications in assessing community-wide health. Community health assessment via BioSCIM could allow rapid assessments and intercomparisons of health status among distinct populations, revealing hidden or emerging trends or disparities and aiding in evaluating correlations (or hypotheses) between stressor exposures and disease.
Published by Elsevier B.V.