title: Estimating nonresponse bias in a telephone-based health surveillance survey in New York City.
abstract: Despite concerns about nonresponse bias due to decreasing response rates, telephone surveys remain a viable option for conducting local population-based surveillance. However, this becomes problematic for urban populations, which typically have higher nonresponse rates. Unfortunately, traditional methods of evaluating nonresponse bias pose challenges for public health practitioners due to high costs. In this study, we sought to increase understanding of survey nonresponse at the zip code level in an urban area and to demonstrate the use of a practical tool for assessing nonresponse bias. Data from the 2008 New York City Community Health Survey, a landline telephone survey of residential households in New York, New York, were matched with zip-code-level data from the 2000 US Census. Although response rates varied across zip codes and zip-code-level sociodemographic characteristics, estimated nonresponse bias for the 5 health measures (general health status, current health insurance coverage, asthma, binge drinking, and physical activity) was not substantial (ranging from -3.8% to 2.4%). Findings confirmed previous research that survey participation rates can vary a great deal across small areas and that there is no direct relationship between response rates and nonresponse bias. This study highlights the importance of assessing nonresponse bias for local urban surveys and demonstrates a workable assessment tool.
authors.forename: Sungwoo
authors.initials: S
authors.lastname: Lim
authors.forename: Stephen
authors.initials: S
authors.lastname: Immerwahr
authors.forename: Sunghee
authors.initials: S
authors.lastname: Lee
authors.forename: Tiffany G
authors.initials: TG
authors.lastname: Harris
mesh_terms: D015982:Bias; D003625:Data Collection / Q000379:methods; D006801:Humans; D009519:New York City; D011159:Population Surveillance / Q000379:methods*; D013689:Telephone
keywords: New York City; bias; health surveys; urban population