RE: "NEIGHBORHOOD ENVIRONMENT AND LOSS OF PHYSICAL FUNCTION IN OLDER ADULTS: EVIDENCE FROM THE ALAMEDA COUNTY STUDY"

Timothy L. Lash and Aliza K. Fink

Department of Epidemiology School of Public Health Boston University Boston, MA 02118

Epidemiologists rely on the mantra that nondifferential misclassification creates an expected bias toward the null, despite several well-known exceptions (15). Perhaps less well known is that only nondifferential and independent misclassification creates an expected bias toward the null (3, 6). When the probability of a subject’s misclassification on one variable (e.g., the exposure) depends on whether the subject was misclassified on a second variable (e.g., the disease), the dependent errors can create substantial bias away from the null even if the overall error rates for both variables are nondifferential (7).

Dependent errors most easily arise when both the exposure and the outcome are measured by the same method, such as an interview with study subjects. Subjects’ thresholds for reporting indicators of exposure and disease may vary for biologic or social reasons, leading to estimates of effect that are biased away from the null by the rearrangement of the true frequencies. A recent investigation of the association between neighborhood environment and physical function in older adults may provide an example. Balfour and Kaplan (8) used self-reported characteristics of the respondent’s neighborhood in 1994 as the exposure variable and self-reported decline in physical function between 1994 and 1995 as the outcome variable. Both neighborhood characteristics and function were undoubtedly measured with some error (6, 9). Measurement of the neighborhood characteristics before the second measurement of physical function suggests that misclassification rates should be nondifferential. However, because both neighborhood characteristics and physical function were measured by self-report, the errors may be dependent. That is, if older respondents who over- or understate their neighborhood problems also over- or understate their physical function, then the estimate of effect may be biased away from the null. Our table 1 shows the observed data and a hypothetically true null association that would give rise to the observed data if only approximately 1.6 percent of the study population overstates neighborhood problems and function and another approximately 1.6 percent understates these variables.


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TABLE 1. Derivation of observed data from a hypothetically null true association
 
Both the authors (8) and the writer of the invited commentary (10) seem ready to infer a causal relation between neighborhood problems and decline in physical function. Certainly the causal relation, were it to hold true, would provide important public health information. However, the potential for dependent errors to account for the observed association also seems plausible. Before accepting the causal relation, we encourage the authors and other stakeholders to consider this competing explanation for the observed association. If they agree that it seems reasonable, then new studies should separate the measurement of neighborhood characteristics from the measurement of function so that dependent errors can be eliminated as an explanation for any observed association.

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