vention (the annual sample size for which is roughly 350,000 adults).9 The epidemiology bureau uses the ACS to generate control totals for post-stratification weighting to produce CHS estimates; this includes splitting the city by borough and each combination of education status, marital status, and household size. Since 2009, the CHS has included a sample from a list of households having only cell phones, not landline phones; Stark indicated that his bureau has used ACS data—and resulting glimpses in change over time—to try to ensure that this cell-phone-only sample is working properly.

Besides the CHS, Stark said that his bureau also helps other parts of DOHMH link to, and use ACS data as supplement to, a variety of other data collections run by the city. These other data collections include both interview based surveys as well as registry/records data, such as special surveys of physical activity and use of public transit options; a specialized analogue of the BRFSS aimed at youth rather than adults (age 18 and older); and a periodic New York version of the National Health and Nutrition Examination Survey (NHANES; the federal version is maintained by the National Center for Health Statistics).

In working with public health surveillance data, Stark noted that DOHMH fashions its approach after the Public Health Disparities Geocoding Project headed by Nancy Krieger of the Harvard School of Public Health. Krieger’s project was discussed and summarized at an earlier National Research Council workshop; see National Research Council (2009: § 2–A.1). Recognizing that socioeconomic status can be an important predictor of disease—linked to neighborhood contextual effects that could be associated with disease—the work estimates area-based poverty measures for geographic pockets throughout the city, using the percentage of residents who live below the federal poverty line. For some of their work, DOHMH uses United Hospital Fund (UHF) areas to approximate neighborhoods; these groupings combine multiple ZIP Code tabulation areas to create (for New York City) about 40 districts that are finer than whole boroughs but larger than individual ZIP Codes. DOHMH anticipates updating these analyses using ACS data, with interest in comparison with similarly defined areas/districts throughout the nation; technically, one question with which they are grappling is the appropriate variety of ACS estimates to use (3- or 5-year estimates).

Stark also outlined an epidemiological study of Legionnaire’s Disease, a form of severe pneumonia that is believed to be transmitted through contaminated water, in which ACS data on occupation proved very useful. DOHMH’s Bureau of Communicable Diseases sought to use its surveillance data on reported cases to examine the hypothesis that occupations potentially associated with contaminated water (e.g., plumbing or air cooling system repair) may re-


9Additional information about the CHS is available from the DOHMH website at [July 2012], while the federal BRFSS is described fully in links from [July 2012].

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