access, utilization, and health outcomes based on such social factors as differences in income, race, ethnicity, and gender. Even when relatively good data can be collected on the outcome of interest—such as infant mortality—and overall trends in that outcome accurately measured, existing data systems do not include sufficient other variables to test what accounts for the observed trends. Moreover, existing data also may not be able to differentiate between overall and subgroup trends. For instance, even though infant mortality rates have decreased for all ethnic and racial groups, disparities between whites and blacks have actually increased. This indicates that the influence on the absolute trends is likely to be different from the influence on the disparities trend (Wise, 2003). Because one of the two goals of Healthy People 2010 is to eliminate disparities, it is important to develop data systems that can measure the effect of policies on health outcome disparities.

A success story in assessing the effect of a major health policy is the national Back to Sleep campaign (Wise, 2003). Because the outcome of interest is infant mortality and because there is a specific long-standing data collection system for this outcome, it has been possible to monitor the effect on sudden infant death syndrome (SIDS) specifically from the time that this national Back to Sleep campaign was introduced (American Academy of Pediatrics Task Force on Infant Position and SIDS, 1992; Pollack and Frohna, 2002; Lesko, Corwin, Vezina, Hunt, Mandel et al., 1998). Using infant mortality data, which contain some information on social class, it was shown that the Back to Sleep educational initiative dramatically reduced mortality rates due to SIDS, but also increased social disparities (Wise, 2003). Research studies were required to demonstrate that the effect of this new information and educational program has a bigger uptake and adoption by wealthier and more educated families. This was an important source of information for national, state, and local policy makers and programs interested in making midcourse corrections in their Back to Sleep campaign.

Measurement of the effect of policies related to the physical environment can be done at several different levels, including the monitoring of air, water and food quality, biomonitoring, and health effects. However, for environmental policy changes, the use of multiple indicators, as shown in Figure 5-1, allows rapid assessment of changes in influences by measuring environmental indices and biomarkers of exposure. These can then be correlated over time with changes in biomarkers of early and late effects, and finally with indicators of health. If a “significant risk” rather than an “actual harm” standard prevails in environmental policy (as it did for leaded gasoline), then biomarkers of exposure, while an indirect measure of children’s health, could be used to document significant risk. The presence of an environmental influence for which there is evidence of likely harm, as measured using biomarkers, can then be used to guide environmental policy decisions.

While Healthy People 2010 provides a possible framework for evaluating the effect of some influences on health, including policy changes, its structure does



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement