| Literature DB >> 15743709 |
Beate Ritz1, Ira Tager, John Balmes.
Abstract
Disease surveillance has a century-long tradition in public health, and environmental data have been collected at a national level by the U.S. Environmental Protection Agency for several decades. Recently, the Centers for Disease Control and Prevention announced an initiative to develop a national environmental public health tracking (EPHT) network with "linkage" of existing environmental and chronic disease data as a central goal. On the basis of experience with long-established disease surveillance systems, in this article we suggest how a system capable of linking routinely collected disease and exposure data should be developed, but caution that formal linkage of data is not the only approach required for an effective EPHT program. The primary operational goal of EPHT has to be the "treatment" of the environment to prevent and/or reduce exposures and minimize population risk for developing chronic diseases. Chronic, multifactorial diseases do not lend themselves to data-driven evaluations of intervention strategies, time trends, exposure patterns, or identification of at-risk populations based only on routinely collected surveillance data. Thus, EPHT should be synonymous with a dynamic process requiring regular system updates to a) incorporate new technologies to improve population-level exposure and disease assessment, b) allow public dissemination of new data that become available, c) allow the policy community to address new and emerging exposures and disease "threads," and d) evaluate the effectiveness of EPHT over some appropriate time interval. It will be necessary to weigh the benefits of surveillance against its costs, but the major challenge will be to maintain support for this important new system. Key words: environmental health, evaluation, intervention, registries, surveillance.Entities:
Mesh:
Year: 2005 PMID: 15743709 PMCID: PMC1253746 DOI: 10.1289/ehp.7450
Source DB: PubMed Journal: Environ Health Perspect ISSN: 0091-6765 Impact factor: 9.031
Challenges for chronic disease surveillance relevant to EPHT.
| Characteristics of the disease |
| Onset can be insidious |
| Exact time of onset not known and often not subject to estimation, which complicate temporal characteristics of exposure |
| Often long latency between onset of exposure and clinical manifestation of disease |
| Heterogeneous mix of phenotypic components (e.g., asthma: allergic, nonallergic, cough variant types) |
| May have multiple natural histories and differ in antecedent exposure profiles (risk factors for onset or recurrence) |
| Genetic heterogeneity may not be reflected in phenotype (e.g., young-onset breast cancers with and without |
| Multiple etiologies; some pathways may not involve the same putative risk factors (e.g., young-onset Parkinson disease caused by MPTP exposure or by Parkin mutations) |
| Characteristics of exposure |
| Often involves complex mixtures that can change over time |
| Relevant parameters often not easily defined |
| Timing of onset |
| Cumulative dose versus critical time of exposure |
| Threshold versus no threshold |
| Effect modification by other exposures |
| Direct measurement often not available |
| Reliance on imperfect surrogates |
MPTP, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine.
Goals and requirements for an EPHT system.
| Surveillance goals | Requirements for health data | Requirements for exposure data | System requirements |
|---|---|---|---|
| Descriptive (ecologic) | Chronic diseases | Long-term exposure assessment | Minimum set of variables for linkage is available (e.g., residential/work address and geocoded exposure location) |
| Temporal | Specificity of diagnosis | Broad spatial coverage that captures medium-scale spatial heterogeneity and should “match” health spatial units as closely as possible | Clear documentation of all variable of changes in format and/or content |
| Spatial | Standardization of diagnostic algorithms over time and procedures to convert from one standard to another (e.g., ICD-9 to ICD-10) | Long historical record keeping and acceptable procedures to convert old to new measurement techniques or metrics | Continued linkage of health and exposure data |
| Moderately short time delays between diagnosis and “registration” (e.g., example within 6 months) | Develop criteria for selection of exposures such as known or suspected health impacts and/or regulatory requirements | Continued dissemination of results to agencies and public | |
| Agreed upon spatial reference (e.g., residence at diagnosis) | Identification of “sentinel” substances where possible | Ongoing administrative, legal, and fiscal support for linkage and dissemination activities | |
| Acute diseases (e.g., poisonings) | Collect data on | ||
| Specificity of diagnosis | Broad categories of sources | ||
| Standardization of diagnostic algorithms over time and procedures to convert from one standard to another (e.g., ICD-9 to ICD-10) | Broad classes of relevant “components” | ||
| Short time delay between identification and registration (e.g., days to weeks) | |||
| Agreed upon spatial reference (e.g., residence at diagnosis) | |||
| Etiologic | Chronic and acute diseases and clusters | Requirements in addition to those mentioned above | Requirements in addition to those mentioned above |
| Chronic | Specificity and standardization (as needed for descriptive purposes) | Near real-time or real-time access to quality-assured data for acute disease and cluster evaluation | Ability to acquire QA/QC and release data consistent with time requirements |
| Acute | Time of registration and spatial reference (as above) | Ability to estimate individual exposure for acute, cluster and chronic disease, or refined spatial and temporal data for acute disease and cluster evaluation | Ability to support special monitoring projects |
| Clusters (spatial and temporal) | Expanded data on risk factors | Data sufficient for spatial and temporal (acute and cumulative) exposure modeling over time for chronic disease | Fiscal and staff support for ongoing modeling |
| Access to noncases for risk factors and exposure | Specific source apportionment in terms of sources and components for acute disease and cluster evaluation | Fiscal support for selected, existing registries and special studies |
Abbreviations: ICD, International Classification of Diseases, 9th and 10th Revisions (WHO 1978, 1993); QA/QC, quality assurance/quality control.
Advantages and disadvantages of various systems for the examination of environmental health questions.
| Registries | Advantages | Disadvantages | Selected examples/references |
|---|---|---|---|
| Disease registries | |||
| Death or birth certificates | Standardized continuous collection of data for the total population in a geographic area
| Outcome data are relatively limited in breadth (i.e., to fatal diseases and few birth outcomes)
| |
| Disease registries (reportable infectious diseases, cancer, end-stage renal disease, and birth defect registries; hospital discharge data; health maintenance organization data) | Standardized continuous collection of data for the total or subgroups of a population in a geographic area
| Laws necessary that mandate reporting and registration
| |
| Exposure/hazard registries | |||
| Ecological exposure registries/databases (air and water pollution, pesticides, industrial emissions inventories) | Standardized continuous collection of exposure data for the total population in a geographic area
| Laws necessary that mandate reporting and registration
| |
| Individual-level exposure registries (biomonitoring, e.g., NHANES) | Collects specific exposure data for a group of select individuals suspected to be exposed at high levels, or for a regional or national random sample of the population
| Very expensive
| |
| Surveys | |||
| Cross-sectional or repeated surveys (NHANES, ISAAC, MONICA, CHIS) | Collect data on one or more diseases and exposures simultaneously for a representative regional, national, or international sample using standardized methods
| One time or repeated high financial investment necessary; costs depend on data collection protocol, sample size, length of observation period, etc.
| |
| Longitudinal cohorts (Framingham study, Nurses’ Health Study, California Teachers Study, Agricultural Health Study) | Collect one or more diseases and exposures over time
| Extremely high financial investment necessary over extended periods; costs depend on data collection protocol, sample size, length of observation period, etc.
| |
Abbreviations: CHIS, California Health Interview Survey; ISAAC, International Study of Asthma and Allergies in Childhood; MONICA, Monitoring of Trends and Determinants in Cardiovascular Diseases.
Issues for expansion and contraction of an EPHT system.
Have scientific data provided compelling new evidence of disease–exposure associations or evidence that previously suspected associations are not causal? Are there new technologies (biomarkers, molecular dosimeters) that indicate the need to updated data collection procedures? Have there been changes in nosology that require new case definitions? Are there new sources of ongoing data collection (routine public health, research cohorts) that offer cost-efficient opportunities to expand surveillance activities? Have there been changes to sources of exposure data that either improve their quality or render them no longer suitable for routine surveillance? Is there public concern about an environmental health issue for which surveillance is the most efficient mechanism to acquire preliminary data? Is there widespread use of a new substance/chemical with the potential for exposing a large population or biopersistence of a substance (e.g., phthalates)? |