Assessing the measurement properties of neighborhood scales: from psychometrics to ecometrics

Am J Epidemiol. 2007 Apr 15;165(8):858-67. doi: 10.1093/aje/kwm040. Epub 2007 Feb 28.

Abstract

Most studies examining the relation between residential environment and health have used census-derived measures of neighborhood socioeconomic position (SEP). There is a need to identify specific features of neighborhoods relevant to disease risk, but few measures of these features exist, and their measurement properties are understudied. In this paper, the authors 1) develop measures (scales) of neighborhood environment that are important in cardiovascular disease risk, 2) assess the psychometric and ecometric properties of these measures, and 3) examine individual- and neighborhood-level predictors of these measures. In 2004, data on neighborhood conditions were collected from a telephone survey of 5,988 residents at three US study sites (Baltimore, Maryland; Forsyth County, North Carolina; and New York, New York). Information collected covered seven dimensions of neighborhood environment (aesthetic quality, walking environment, availability of healthy foods, safety, violence, social cohesion, and activities with neighbors). Neighborhoods were defined as census tracts or census clusters. Cronbach's alpha coefficient ranged from 0.73 to 0.83, with test-retest reliabilities of 0.60-0.88. Intraneighborhood correlations were 0.28-0.51, and neighborhood reliabilities were 0.64-0.78 for census tracts for most scales. The neighborhood scales were strongly associated with neighborhood SEP but also provided information distinct from neighborhood SEP. These results illustrate a methodological approach for assessing the measurement properties of neighborhood-level constructs and show that these constructs can be measured reliably.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Aged
  • Cardiovascular Diseases / epidemiology*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Models, Econometric
  • Psychometrics
  • Residence Characteristics / statistics & numerical data*
  • Risk Assessment
  • Socioeconomic Factors*
  • United States / epidemiology