Literature DB >> 23985129

Estimating nonresponse bias in a telephone-based health surveillance survey in New York City.

Sungwoo Lim, Stephen Immerwahr, Sunghee Lee, Tiffany G Harris.   

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.

Entities:  

Keywords:  New York City; bias; health surveys; urban population

Mesh:

Year:  2013        PMID: 23985129     DOI: 10.1093/aje/kwt121

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  5 in total

1.  Measurement error of self-reported physical activity levels in New York City: assessment and correction.

Authors:  Sungwoo Lim; Brett Wyker; Katherine Bartley; Donna Eisenhower
Journal:  Am J Epidemiol       Date:  2015-04-08       Impact factor: 4.897

2.  An evaluation of patient experience during percutaneous breast biopsy.

Authors:  Jean M Seely; Fraser Hill; Susan Peddle; Jackie Lau
Journal:  Eur Radiol       Date:  2017-05-22       Impact factor: 5.315

3.  Design and respondent selection of a population-based study on associations between breast cancer screening, lifestyle and quality of life.

Authors:  Tytti Sarkeala; Sirpa Heinävaara; Jonna Fredman; Satu Männistö; Riitta Luoto; Maija Jäntti; Nea Malila
Journal:  BMC Public Health       Date:  2015-12-18       Impact factor: 3.295

4.  Non-response bias in estimates of prevalence of club-based sport participation from an Australian national physical activity, recreation and sport survey.

Authors:  J T Harvey; M J Charity; N A Sawyer; R M Eime
Journal:  BMC Public Health       Date:  2018-07-18       Impact factor: 3.295

5.  Cancer patients' participation in population-based health surveys: findings from the HUNT studies.

Authors:  Sophie D Fosså; Alv A Dahl; Arnulf Langhammer; Harald Weedon-Fekjær
Journal:  BMC Res Notes       Date:  2015-11-05
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.