PURPOSE: There is growing interest in incorporating area indicators into epidemiologic analyses. Using data from the 1990 U.S. Census linked to individual-level data from three epidemiologic studies, we investigated how different area indicators are interrelated, how measures for different sized areas compare, and the relation between area and individual-level social position indicators. METHODS: The interrelations between 13 area indicators of wealth/income, education, occupation, and other socioenvironmental characteristics were investigated using correlation coefficients and factor analyses. The extent to which block-group measures provide information distinct from census tract measures was investigated using intraclass correlation coefficients. Loglinear models were used to investigate associations between area and individual-level indicators. RESULTS: Correlations between area measures were generally in the 0.5--0.8 range. In factor analyses, six indicators of income/wealth, education, and occupation loaded on one factor in most geographic sites. Correlations between block-group and census tract measures were high (correlation coefficients 0.85--0.96). Most of the variability in block-group indicators was between census tracts (intraclass correlation coefficients 0.72--0.92). Although individual-level and area indicators were associated, there was evidence of important heterogeneity in area of residence within individual-level income or education categories. The strength of the association between individual and area measures was similar in the three studies and in whites and blacks, but blacks were much more likely to live in more disadvantaged areas than whites. CONCLUSIONS: Area measures of wealth/income, education, and occupation are moderately to highly correlated. Differences between using census tract or block-group measures in contextual investigations are likely to be relatively small. Area and individual-level indicators are far from perfectly correlated and provide complementary information on living circumstances. Differences in the residential environments of blacks and whites may need to be taken into account in interpreting race differences in epidemiologic studies.

BACKGROUND: Large international variations in rates of prostate cancer incidence and mortality suggest that environmental factors have a strong influence on the development of this disease. The purpose of this study was to identify predictive variables for prostate cancer mortality in data from 59 countries. METHODS: Data on prostate cancer mortality, food consumption, tobacco use, socioeconomic factors, reproductive factors, and health indicators were obtained from United Nations sources. Linear regression models were fit to these data. The influence of each variable fit in the regression models was assessed by multiplying the regression coefficient b by the 75th (X75) and 25th (X25) percentile values of the variable. The difference, bX75 - bX25, is the estimated effect of the variable across its interquartile range on mortality rates measured as deaths per 100000 males aged 45-74 years. Reported P values are two-sided. RESULTS: Prostate cancer mortality was inversely associated with estimated consumption of cereals (bX75 - bX25 = -7.31 deaths; P = .001), nuts and oilseeds (bX75 - bX25 = -1.72 deaths; P = .003), and fish (bX75 - bX25 = -1.47 deaths; P = .001). In the 42 countries for which we had appropriate data, soy products were found to be significantly protective (P = .0001), with an effect size per kilocalorie at least four times as large as that of any other dietary factor. Besides variables related to diet, we observed an association between prostate cancer mortality rates and a composite of other health-related, sanitation, and economic variables (P = .003). CONCLUSIONS: The specific food-related results from this study are consistent with previous information and support the current dietary guidelines and hypothesis that grains, cereals, and nuts are protective against prostate cancer. The findings also provide a rationale for future study of soy products in prostate cancer prevention trials.

BACKGROUND: The National Children's Study is the most ambitious study ever attempted in the United States to assess how environmental factors impact child health and development. It aims to follow 100,000 children from gestation until 21 years of age. Success requires breaking new interdisciplinary ground, starting with how to select the sample of > 1,000 children in each of 105 study sites; no standardized protocol exists for stratification of the target population by factoring in the diverse environments it inhabits. Worcester County, Massachusetts, like other sites, stratifies according to local conditions and local knowledge, subject to probability sampling rules. OBJECTIVES: We answer the following questions: How do we divide Worcester County into viable strata that represent its health-relevant environmental and sociodemographic heterogeneity, subject to sampling rules? What potential does our approach have to inform stratification at other sites? RESULTS: We developed a multivariable, vulnerability-based method for spatial sampling consisting of two descriptive indices: a hazards/stressors exposure index (comprising three proxy variables), and an adaptive capacity/sociodemographic character index (five variables). Multivariable, health-relevant stratification at the start of the study may improve detection power for environment-child health associations down the line. Eighteen strata capture countywide heterogeneity in the indices and have optimal relative homogeneity within each. They achieve comparable expected birth counts and conform to local concepts of space. CONCLUSION: The approach offers moderate to high potential to inform other sites, limited by intersite differences in data availability, geodemographics, and technical capacity. Energetic community engagement from the start promotes local stratification coherence, plus vital researcher-community trust and co-ownership for sustainability.