The authors investigated the rate of gestational weight gain associated with the lowest combined risk of 5 short- and longer-term maternal and child health outcomes for 2,012 mother-child pairs recruited in 1999-2002 into Project Viva, a prebirth cohort study in Massachusetts. Within each maternal prepregnancy body mass index (BMI, kg/m(2)) stratum, they performed a logistic regression analysis predicting all 5 outcomes, from which they determined the rate of gain at which average predicted prevalence of the adverse outcomes was the lowest. The mean rate of total gestational weight gain was 0.39 kg/week (standard deviation, 0.14). The prevalence of small for gestational age was 6%, large for gestational age was 14%, preterm delivery was 7%, substantial postpartum weight retention was 16%, and child obesity was 10%. The lowest predicted outcome prevalence occurred with a 0.28-kg/week gain for women whose BMI was 18.5-24.9, a 0.03-kg/week loss for a BMI of 25.0-29.9, and a 0.19-kg/week loss for a BMI of >or=30.0 kg/m(2)--the lowest observed weight changes in overweight and obese women. For normal-weight and overweight women, lowest-risk gains varied modestly with adjustment for maternal characteristics and with different outcome weightings. For obese women, the lowest-risk weight change was weight loss in all models. Recommendations for gestational weight gain for obese women should be revised.

The income elasticity of the value per statistical life (VSL) is an important parameter for policy analysis. Mortality risk reductions often dominate the quantified benefits of environmental and other policies, and estimates of their value are frequently transferred across countries with significantly different income levels. U.S. regulatory agencies typically assume that a 1.0 percent change in real income over time will lead to a 0.4 to 0.6 percent change in the VSL. While elasticities within this range are supported by substantial research, they appear nonsensical if applied to populations with significantly smaller incomes. When transferring values between high and lower income countries, analysts often instead assume an elasticity of 1.0, but the resulting VSL estimates appear large in comparison to income. Elasticities greater than 1.0 are supported by research on the relationship between long-term economic growth and the VSL, by cross-country comparisons, and by new research that estimates the VSL by income quantile. Caution is needed when applying these higher elasticities, however, because the resulting VSLs appear smaller than expected future earnings or consumption in some cases, contrary to theory. In addition to indicating the need for more research, this comparison suggests that, in the interim, VSL estimates should be bounded below by estimates of future income or consumption.

The estimates used to value mortality risk reductions are a major determinant of the benefits of many public health and environmental policies. These estimates (typically expressed as the value per statistical life, VSL) describe the willingness of those affected by a policy to exchange their own income for the risk reductions they experience. While these values are relatively well studied in high-income countries, less is known about the values held by lower-income populations. We identify 26 studies conducted in the 172 countries considered low- or middle-income in any of the past 20 years; several have significant limitations. Thus there are few or no direct estimates of VSL for most such countries. Instead, analysts typically extrapolate values from wealthier countries, adjusting only for income differences. This extrapolation requires selecting a base value and an income elasticity that summarizes the rate at which VSL changes with income. Because any such approach depends on assumptions of uncertain validity, we recommend that analysts conduct a standardized sensitivity analysis to assess the extent to which their conclusions change depending on these estimates. In the longer term, more research on the value of mortality risk reductions in low- and middle-income countries is essential.

Public risk perceptions and demand for safer food are important factors shaping agricultural production practices in the United States. Despite documented food safety concerns, little attempt has been made to elicit consumers' subjective risk judgments for a range of food safety hazards or to identify factors most predictive of perceived food safety risks. In this study, over 700 conventional and organic fresh produce buyers in the Boston area were surveyed for their perceived food safety risks. Survey results showed that consumers perceived relatively high risks associated with the consumption and production of conventionally grown produce compared with other public health hazards. For example, conventional and organic food buyers estimated the median annual fatality rate due to pesticide residues on conventionally grown food to be about 50 per million and 200 per million, respectively, which is similar in magnitude to the annual mortality risk from motor vehicle accidents in the United States. Over 90% of survey respondents also perceived a reduction in pesticide residue risk associated with substituting organically grown produce for conventionally grown produce, and nearly 50% perceived a risk reduction due to natural toxins and microbial pathogens. Multiple regression analyses indicate that only a few factors are consistently predictive of higher risk perceptions, including feelings of distrust toward regulatory agencies and the safety of the food supply. A variety of factors were found to be significant predictors of specific categories of food hazards, suggesting that consumers may view food safety risks as dissimilar from one another. Based on study findings, it is recommended that future agricultural policies and risk communication efforts utilize a comparative risk approach that targets a range of food safety hazards.

The role of models to support recommendations on the cost-effective use of medical technologies and pharmaceuticals is controversial. At the heart of the controversy is the degree to which experimental or other empirical evidence should be required prior to model use. The controversy stems in part from a misconception that the role of models is to establish truth rather than to guide clinical and policy decisions. In other domains of public policy that involve human life and health, such as environmental protection and defense strategy, models are generally accepted as decision aids, and many models have been formally incorporated into regulatory processes and governmental decision making. We formulate an analytical framework for evaluating the role of models as aids to decision making. Implications for the implementation of Section 114 of the Food and Drug Administration Modernization Act (FDAMA) are derived from this framework.