Guidance for Screening the Impact Study Area for Presence of an Environmental Justice Area Based on Health Outcome Data
Section 487.5(c) of Subpart H (Chapter IV of Title 6 NYCRR)
(c) If no area meeting the definition of either a minority or low-income community is present within the Impact Study Area, an EJ area is present if:
(1) a census block group or contiguous area with multiple census block groups has a minority or low-income population that is above 75% of the stated thresholds for defining a minority or low-income community, and
(2) (i) reasonably available air quality data and (ii) health outcome data that have been made available to the public statewide at the zip code level, reveals that the Impact Study Area may bear a disproportionate share of the negative environmental consequences resulting from industrial, municipal, and commercial operations or the execution of federal, state, local, and tribal programs and policies, when compared to the county as a whole, or if the Impact Study Area is in the City of New York, when compared to the city as a whole. In the case of health outcome data, applicants shall consult with the Department of Health about appropriate comparison areas for specific datasets.
To screen an impact study area for the presence of an environmental justice area, a health outcome can only be used if:
- there are statewide data available to the public at the ZIP code level,
- the health outcome has enough occurrences to result in stable rates (see discussion on Rates Based on Small Numbers), and
- areas with the highest rates can be identified (by examining rates by quartiles within the state, within New York City, or within New York State exclusive of New York City; or by some other method).
Health outcomes that DOH has selected for this screening method include asthma emergency department visits, certain sites of cancer, and low birth weight. This list may be updated with additional outcomes at a later date.
ZIP code data on DOH public website relevant to these outcomes:
The use of asthma emergency department (ED) visits rather than hospital discharges is recommended because emergency department visits include hospital discharges and provide greater numbers and therefore more stable rates for statistical analysis. There are small numbers of hospital discharges for many ZIP codes outside of New York City (NYC) and for some within NYC. Tables and maps of ED visits by ZIP code are available at www.health.ny.gov/statistics/ny_asthma/ed/ZIPcode/map.htm; for each ZIP code, the number of asthma ED visits in a three-year period, annual population for the middle year, and asthma ED visit rate are provided. Quartiles for the asthma ED visit rate for NYS, exclusive of NYC and for NYC have been developed and can be found in the map legend.1 ZIP codes with the highest rates are in quartile 4. For the purpose of this screening method, an asthma ED visit rate in quartile 4 is considered an indicator for disproportionate asthma burden. The asthma ED visit rate for an impact study area in NYC should be compared to the cut-off for quartile 4 for NYC, and the asthma ED visit rate for an impact study area outside of NYC should be compared to the cut-off for quartile 4 for NYS, exclusive of NYC.
- Impact study area that is a single ZIP code: the asthma ED visit rate for the ZIP code can be found in the table and compared to the cut-off for quartile 4.
- Impact study area made up of multiple ZIP codes: for the relevant ZIP codes, select from the table of asthma ED visits, the number of ED visits during the three-year period and the annual population. Sum each of the columns to determine the total number of asthma ED visits for the impact study area and the annual population for the impact study area. Calculate the asthma ED visit rate for the impact study area: [(no. ED visits ÷ 3) ÷ annual population] x 10,000. This rate can be compared with the cut-off for quartile 4 found in the map legend.
- Under the New York State Cancer Surveillance Improvement Initiative, DOH displays observed and expected numbers of cancer cases by ZIP code for cancer for colorectal and lung/bronchus cancer in males and females, female breast cancer, and prostate cancer. A column also shows percent different from expected (within 15% of expected, 15%-50% below expected, more than 50% below expected, 15%-49% above expected, 50%-100% above expected, and very sparse data). A notation of "50% to 100% above expected" could be considered an indicator of a disproportionate burden of that type of cancer.
- NYSDOH's Environmental Facilities and Cancer Mapping web page provides information on many different types of cancer (currently 23). Different types of cancer have different causes, and there are many factors that affect a person's chances of getting different types of cancer. Not all of these types of cancer have been found to be related to environmental exposures or have disparities based on race/ethnicity and poverty. More information about the specific types of cancer and their risk factors can be found at www.health.ny.gov/statistics/cancer/registry/abouts/. The map shows highlighted areas of New York State where cancer is higher or lower than expected during a certain period based on the cancer rate for the entire state. In areas shaded pink, there were 50 percent more observed cases than expected; in areas shaded blue, there were 50 percent fewer observed cases than expected. To see whether the impact study area is in a pink shaded area where cancer was higher than expected, zoom in on the impact study area on the map, and select a type of cancer.
- Low birth weight
Data on low birth weight by ZIP code can be found in the New York State County/ZIP Code Perinatal Data Profiles. The total number of births and percent of low birth weight births are displayed for a three-year period. Quartiles for low birth weight by ZIP code have not yet been developed. However, reference percentages have been derived from the table of low birth weight by county: the percentage of low birth weight births for 2008-2010 for New York City was 8.7 (see Region 7-NYC total), and for New York State exclusive of New York City was 7.7. (The percentage for New York State exclusive of New York City was derived by subtracting the number of low birth weight births and the average number of births for Region 7-NYC from those for New York State, and calculating percent low birth weight.) These reference percentages will be used to determine disproportionate low birth weight burden until quartiles are developed.
- Impact study area that is a single ZIP code: in the New York State County/ZIP Code Perinatal Data Profiles, select the appropriate county on the map, and find the relevant ZIP code. Look for the percentage of low birth weight births for the relevant ZIP code and compare that percentage to the reference percentage provided in the previous paragraph for New York State exclusive of NYC if the impact study area is outside of NYC, and for NYC if the impact study area is within NYC. If the percentage of low birth weight for the impact study area is equal to or lower than the appropriate reference percentage, then the impact study area does not have a disproportionate burden for low birth weight. If the percentage of low birth weight births for the impact study area is higher than the reference percentage, contact NYSDOH (email@example.com) for further guidance.
- Impact study area made up of multiple ZIP codes: a percentage of low birth weight births for the combined area of the ZIP codes must be calculated from the information in the New York State County/ZIP Code Perinatal Data Profile. Select the appropriate county (or counties) from the state map and find the relevant ZIP codes. Create a table for the relevant ZIP codes with a column for ZIP code, a column for total births in ZIP code, and a column for percent of low birth weight births (fill in the total births in ZIP code and percent of low birth weight births from the table on the website). Create an additional column for number of low birth weight births and fill it in by performing the following calculation. For each ZIP code, divide the percentage of low birth weight births by 100, and multiply by the number of total births. Round to the nearest whole number. Sum that column to find the total number of low birth weight births in the impact study area. Sum the column labeled "total births in ZIP code" to find the total number of births in the impact study area. Compute the percentage of low birth weight births for the impact study area by dividing the total number of low birth weight births in the impact study area by the total number of births in the impact study area, and multiplying by 100. Compare this percentage to the appropriate reference percentage as described in the previous paragraph.
- 1Quartiles were developed separately for NYC and for NY State exclusive of NYC. Quartiles are based on the number of ZIP codes, e.g., for NYC each quartile contains one-fourth of the ZIP codes in NYC.
For questions regarding health data review under DEC regulations 6NYCRR Part 487, e-mail firstname.lastname@example.org.