Evaluating options for measurement of neighborhood socioeconomic context: Evidence from a myocardial infarction case–control study

Abstract

We hypothesized that neighborhood socioeconomic context would be most stronly associated with risk of myocardial infarction (MI) for smaller "neighborhood" definitions. We used data on 487 nonfatal, incident MI cases and 1,873 controls from a case-control study in Washington State. Census data on income, home ownership, and education were used to estimate socioeconomic context across four neighborhood definitions: one-kilometer buffer, block group, census tract, and ZIP code. No neighborhood definition led to consistently stronger associations with MI. Although we confirmed the association between neighborhood socioeconomic measures and risk of MI, we did not find these associations sensitive to neighborhood definition. Gina Lovasi, PhD, 820 IAB, MC 3355, 420 W 118th St, New York NY 10027, 212-854-3804 (office), 646-761-1362 (mobile), 212-854-8925 (fax), gl2225@columbia.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Socioeconomic disparities in health have received increasing attention by researchers (Adler and Ostrove, 1999) and policy makers (Mackenbach and Bakker, 2003) in recent decades. Socioeconomic status (SES) has been posited to be a "fundamental cause" of health disparities (Phelan et al., 2004, Williams andCollins, 2001), such that the association between SES and health is created when higher status individuals or groups mobilize flexible resources, such as money and prestige, to avoid illness and death. There is also evidence from human and animal studies that psychosocial stress in response to relative social status contributes to mortality and disease for low status individuals (Wilkinson,1999, Steptoe andMarmot, 2002) and those living in more deprived areas (Elliott, 2000). Socioeconomic characteristics measured for individuals and areas have commonly included the domains of education, employment, occupational status, income, and material resources (Braveman et al., 2005, Krieger et al., 2002a, Carstairs, 2000. The questionnaires or other methods used to ascertain such characteristics differ across settings and studies (Krieger et al., 1997), and area-based socioeconomic characteristics have the additional complication of being measured at different scales or levels of aggregation (Pickett and Pearl, 2001). NIH Public AccessIn studies of neighborhood socioeconomic context and health, several scales of measurement are used without consensus as to which is most relevant. The modifiable areal unit problem, like the ecological fallacy, is a concern for such studies because study results may be sensitive to the selected measurement scale (Guagliard...

Small and large size for gestational age and neighborhood deprivation measured within increasing proximity to homes

“…We explored differences in model fit at each neighborhood size. As in a simulation study (Spielman and Yoo, 2009) and a previous empirical study (Lovasi, et al, 2008), buffer size had little impact on model fit. Furthermore, model fit for White women was much higher than for minority race/ethnic groups (Table 3).…”

“…For example, if estimated effects of NDI measured within the 8 km buffer size were particularly strong, our findings would provide evidence that NDI may operate on a large scale, and that the 8 km buffer was suitable for measuring neighborhood deprivation. Simulation (Spielman and Yoo, 2009) and an empirical study (Lovasi, et al, 2008) suggest that model fit has minimal utility as a criterion for the most appropriate neighborhood definition. We present overall model fit as corroboration of these prior findings, but focus discussion on the strength of the adjusted association.…”

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“…The use of zip codes as an indicator for area-based socioeconomic context has received criticism in the scientific literature due to variations over time, size inconsistencies, and the neglect of other political, statistical or administrative boundaries 48. However, recent research has found that associations at the zip code level were similar to those found at smaller geographic definitions of neighborhood such as census tract and census block group levels 49–50. Regardless of this support for the use of matching zip codes, we recognize that residual confounding could still occur and is a limitation of this study.…”

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“…We use Wald tests to perform both sets of tests, and Appendix A.3 provides details on the test statistics. Smith et al (1995), Sobal et al (1996), Krieger et al (1999), Reijneveld et al (2000), Lorant et al (2001), Auchincloss and Hadden (2002), Flowerdew et al (2008), and Lovasi et al (2008) are all examples of work where using a Wald test statistic to test equality of estimates across different model specifications would have been useful; we found no examples in the literature where Wald tests were used.…”