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In November 2002, the National Center for Healthy Housing convened a 2-day workshop to review the state of knowledge in the field of healthy housing. The workshop, supported with funds from the U.S. Centers for Disease Control and Prevention’s National Center for Injury Prevention and Control and National Center for Environmental Health, was unique in that it focused solely on the effect of housing on children’s health and the translation of research findings into practical activities in home construction, rehabilitation, and maintenance. Participants included experts and practitioners representing the health, housing, and environmental arenas. Presentations by subject-matter experts covered four key areas: asthma, neurotoxicants, injury, and translational research. Panel discussions followed the presentations, which generated robust dialogue on potential future research opportunities and overall policy gaps. Lack of consensus on standard measurements, incomplete understanding about the interaction of home hazards, inadequate research on the effectiveness of interventions, and insufficient political support limit current efforts to achieve healthy housing. However, change is forthcoming and achievable.

Results of the analyses of occupational and environmental samples are frequently reported as "less than a specified value," a practice followed by many analytical laboratories. A left-censored distribution occurs when analytical laboratories do not report results that fall below their limits of detection or quantification. Approximately 37% of the household interior dust lead loadings collected in a large-scale, multisite, longitudinal study of lead-based paint hazard controls were reported to be below the "method detection limit." These unreported values are unusable in any statistical analysis of the data and must be replaced by a valid dust lead loading estimate, a process called data imputation. This investigation tested how well data imputed using a newly formulated procedure for estimating the data below the method detection limit were correlated with dust lead loadings reported by the participating laboratories after special request. These results were also compared with those obtained by imputing the minimum detectable level by the square root of 2. Imputation of the low lead loadings was accomplished by substituting the value associated with the median percentile below each laboratory's method detection limit. A correlation of r = 0.50 was calculated between the predicted and reported dust lead loadings, with only slight bias (2.9%) in the predicted values. An alternative imputation procedure that used the predicted value from structural equation models fit to the noncensored dust lead loadings performed about as well, although the predictions had to be "centered" to correspond to the censored data. An estimator that combined both of these imputation procedures only slightly improved the correlation between the predicted and laboratory values (r = 0.51). These results support the use of the new procedure rather than the commonly used imputed values of the method detection limit divided by 2 or by the square root of 2. Imputing values based on either of these common approaches may result in much more biased predictions for the censored data; in the case of these data, the dust lead loadings were overestimated by 348%. The results also suggest that analytical laboratories should provide a numerical result for all analyzed samples, with a "flag" of those values below their detection limit, since these results may be more accurate than any imputed value, particularly those provided by the commonly used method of dividing the minimum detection limit by the square root of 2.

Mortality among 5,413 white males who were employed for at least two years at a plutonium weapons facility was investigated to measure risks from exposures to low levels of plutonium and external radiation. When compared with US death rates, fewer deaths than expected were found for all causes of death, all cancers, and lung cancer. No bone cancer was observed. An excess of brain tumors was found for the cohort in general. Elevated rate ratios for all causes of death and all lymphopoietic neoplasms were found when employees with plutonium body burdens greater than or equal to 2 nCi were compared with those with body burdens less than 2 nCi, while accounting for age, calendar period, and induction time. Increased rate ratios were also found for esophageal, stomach, colon, and prostate cancers, and for lymphosarcomas and reticulum cell sarcomas. No elevated rate ratios were noted for bone and liver cancers. When employees with cumulative exposures greater than or equal to 1 rem were compared with those with exposures less than 1 rem, elevated rate ratios were found for myeloid leukemia, lymphosarcoma and reticulum cell sarcoma, liver neoplasms, and unspecified brain tumors. No overall dose-response relationships were found for plutonium or external radiation exposures. Standardized rate ratios increased, however, as plutonium body burden levels increased for all causes, all cancers, and digestive cancers at five years induction time. Standardized rate ratios also increased as external radiation exposure categories increased for all lymphopoietic cancers and unspecified brain tumors for a two-year induction period. With the exception of analyses of combined categories of death, and perhaps of lung cancer, confidence limits were wide, indicating limited precision. Nevertheless, these findings suggest that increased risks for several types of cancers cannot be ruled out at this time for individuals with plutonium body burdens of greater than or equal to 2 nCi. Plutonium-burdened individuals should continue to be studied in future years.