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Tracking (NM EPHT) Methods

Network Data Processing Integration and Analysis

The New Mexico Environmental Public Health Tracking (EPHT or Tracking) program has been a part of the National program since its start in 2002. We have contributed to, helped develop and enhance the Nationally Consistent Data and Measures (NCDMs) and the national and state portals, towards a better understanding of health and environmental data through use and integration. These integrated data drive actions to improve the health of our communities. The National Tracking Network is a national, state, and local web-based system. Components are updated annually and are continuously assessed to prioritize environmental health issues, to formulate key surveillance and research questions, and to evaluate the utility of existing data for answering those questions.

Acquire Health and Environmental Data

Tracking human health and environmental quality requires diverse data types. We collect and display New Mexico birth defects and birth outcomes, select emergency and inpatient (hospitalizations) morbidity, select cancer incidence, and deaths as well as human exposure through calls to the NM Poison Center and elevated blood lead levels in children. On the environmental side we display air quality, climate variables, and water quality. The data we display is the result of twenty years of ongoing, collaborative work of state and federal toxicologists, epidemiologists, environmentalists, ecologists, communications specialists, governmental data stewards and information technology experts to build state and national websites. The websites provide standardized, user-friendly information on the NCDM indicators of health and environment, relevant and timely news and updates, precise details about the measures (see metadata and indicator reports) and flexible online queries of environmental and health data. As information on health and the environment continues to mature and modernize, we add new measures and analyses.

The first step in creating an NCDM is the acquisition of existing data and the development of methods to use those data for public health while not exposing individual information. This is crucial for the sharing of state data with the federal agency reflecting on the status of environmental public health. Sharing data are necessary because the Centers for Disease Control (CDC) access much of the state's health data.

Data are under the stewardship of many independent and separate government entities. Agreements on the use of the data assure against inappropriate use and disclosure of sensitive information. Most of the Tracking data are presented on the 25 state and 1 city portals and CDC's National Environmental Public Health Tracking.

Health Data

Births, Birth Outcomes, and Deaths


Carbon Monoxide Poisoning Exposures

Childhood Lead Poisoning

Morbidity, Emergency and Hospital Care

Environmental Data




Nationally Consistent Data and Measures (NCDMs), Indicator Reports, and Metadata


The data acquired are used to populate the NCDMs (see the Data Portal above) and for the development of new measures. Detailed information on the NCDMs can be found in the Indicator Reports and Metadata.

Indicator Reports

Each NCDM has an associated indicator report that provides definition(s), context on why the measure (indicator) is important, related measures and data views on numbers, rates, age-adjusted rates and related demographics and seasonal views, where relevant. Indicator reports provide core information on the measures, whereas queries provide more general or specific information with many parameters selected by the user. Indicator reports are indexed and accessible through the Data Portal tab at the top.


Metadata are "data about data." NM Tracking makes extensive use of descriptive metadata, which allow a user to learn the what, why, when, who, where, and how for a data resource. It may reference additional information like quality assurance documents and data dictionaries. Like measure specific indicator reports, measure specific metadata are indexed and readily accessible through the Data Portal tab at the top.

Advanced Epidemiological Methods

Integrating Health and Environmental Data Measures by Space (Geocoding), Time, and Ecology

Integration of health and environmental measures requires compatible data. As data come to NM Tracking from various sources, most data sets arrive in different formats. For example, some files will have "sex" designated as "M," "F," or "Unknown" while others will have "0," "1," "2," or "9." These and other, more extreme, differences must be resolved before we can proceed to integration and analysis. Therefore, NM Tracking expends an enormous amount of time and energy in quality assurance before integration even begins. Once prepared, data may be integrated and analyzed.

Linking Health and Environmental Data

Ecological linkage studies are investigations that connect environmental and health outcome data in time and place within a population. A good example of the impact such studies may have been the requirement of the removal of lead from gasoline in the 1970's, following a series of national linkage studies showing that blood lead levels decreased as lead use in gasoline declined. A clear cause-effect relationship existed between an environmental hazard and a health effect and measuring the declining lead content of gasoline was relatively easy to do. Tracking linkages are largely done spatially through geocoding of places of exposure and illness and linking in time.


Geocoding health outcomes and environmental data assigns geographic locators to the data, thus enabling spatial linkage across data types. Most of our data are geocoded with latitude-longitude coordinates assigned to a street address. Street address, city, county, zip code, and census tract are typically used to geocode Tracking data.

Unfortunately, for many diseases the cause-effect relationship is not clear, and environmental hazards cannot be measured easily. Furthermore, many adverse health outcomes may result from exposures to multiple different hazards, some received in the short term and others received over a longer, more protracted time period. For these reasons, it is important that linkage be approached in a scientifically rigorous manner. However, even here, caution is needed in the interpretation of results since the environmental data used in linkage analysis ordinarily is not collected on an individual basis; rather, data are collected across broad populations, such as a county or particular region within a state, unless geocoded addresses are available and that location information re-linked with the originating record. Consequently, a study that does find a relationship between the level of an environmental hazard and the occurrence of a health outcome cannot be used to conclude that the hazard caused the health outcome, since it is not known who among the population received exposure at the levels of interest. Rather, the results of such studies can be used to generate hypotheses on causation, which can then be tested in more formal studies involving recruitment of study subjects and collection of data on an individual level or analytical approaches allow for ecological, statical, linkages.

Analyses Measures: Counts, Rates, and Age Adjustment

Rates are intended to scale health issues to the population, but counts have meaning as well. We attempt to provide perspective by making counts and rates available in addressing an indicator. However, the rate of a health problem may not communicate the simple message that the health outcome is avoidable. For example, carbon monoxide poisoning is absolutely and easily preventable.

Rates might require adjusting due to factors such as age. If groups differ with respect to this factor, rates cannot be appropriately compared unless adjusted. For age, the general practice is to adjust rates to a standard population (e.g., the United States population from the 2000 Census). Using this practice, the mortality rates for New Mexico and Alaska would both be age-adjusted to the U.S. standard population. The mortality rates could then be compared.

For mortality, age adjustment is calculated as follows:
  1. Choose a standard population with a known distribution (U.S. Census 2000 Population).
  2. Calculate the age-specific death rates for the two populations (e.g., New Mexico and Alaska).
  3. Calculate the age-specific expected number of deaths based on the standard population (multiply the age-specific death rates for the two states by the number of people in the respective age class in the standard population).
  4. For each state, add the expected numbers of deaths over all age classes. Divide the resulting total number of expected deaths by the total number of people in the standard population. These are the age-adjusted death rates.

Age-adjusted rates are used for many health outcomes on NM Tracking but are not always the preferred method for comparison. There are health conditions that require adjusting to non-standard population measures. For example, the most useful rate for acute myocardial infarction (AMI) is for those aged 35 and older.