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Objectives. We examined whether the interactions between primarily speaking English at home and community-level measures (median household income and immigrant composition) are associated with physical inactivity and obesity. Methods. We pooled the 2005 and 2007 Los Angeles County Health Survey data to construct a multilevel data set, with community-level median household income and immigrant density as predictors at the community level. After controlling for individual-level demographic variables, we included the respondent's perceived community safety as a covariate to test the hypothesis that perceived public safety mediates the association between acculturation and health outcomes. Results. The interaction between community median household income and primarily speaking English at home was associated with lower likelihoods of physical inactivity (odds ratio [OR] = 0.644; 95% confidence interval [CI] = 0.502, 0.825) and obesity (OR = 0.674; 95% CI = 0.514, 0.882). These odds remained significant after we controlled for perceived community safety. Conclusions. Resources in higher-income areas may be beneficial only to residents fully integrated into the community. Future research could focus on understanding how linguistic isolation affects community-level social learning and access to resources and whether this differs by family-level acculturation. [ABSTRACT FROM AUTHOR]

Objectives. In order to comprehensively examine the risks and resources associated with racial-ethnic disparities in adverse obstetric outcomes, the Los Angeles County Department of Public Health and the University of California, Los Angeles, joined efforts to design and implement the 2007 Los Angeles Mommy and Baby (LAMB) study. This paper aims to present the conceptual frameworks underlying the study's development, highlight the successful collaboration between a research institution and local health department, describe the distinguishing characteristics of its methodology, and discuss the study's implications for research, programs, and policies. Methods. The LAMB study utilized a multilevel, multistage cluster design with a mixed-mode methodology for data collection. Two samples were ultimately produced: the multilevel sample (n = 4,518) and the augmented final sample (n = 6,264). Results. The LAMB study allowed us to collect multilevel data on the risks and resources associated with racial-ethnic disparities in adverse obstetric outcomes. Both samples were more likely to be Hispanic, aged 20-34 years, completed at least 12 years of schooling, and spoke English. Conclusions. The LAMB study represents the successful collaboration between an academic institution and local health department and is a theoretically based research database and surveillance system that informs effective programmatic and policy interventions to improve outcomes among LAC's varied demographic groups. [ABSTRACT FROM AUTHOR]

Background: The Mayo Lung Project (MLP), a randomized controlled clinical trial of lung cancer screening conducted between 1971 and 1986 among male smokers aged 45 or above, demonstrated an increase in lung cancer survival since the time of diagnosis, but no reduction in lung cancer mortality. Whether this result necessarily indicates a lack of mortality benefit for screening remains controversial. A number of hypotheses have been proposed to explain the observed outcome, including over-diagnosis, screening sensitivity, and population heterogeneity (initial difference in lung cancer risks between the two trial arms). This study is intended to provide model-based testing for some of these important arguments. Method: Using a micro-simulation model, the MISCAN-lung model, we explore the possible influence of screening sensitivity, systematic error, over-diagnosis and population heterogeneity. Results: Calibrating screening sensitivity, systematic error, or over-diagnosis does not noticeably improve the fit of the model, whereas calibrating population heterogeneity helps the model predict lung cancer incidence better. Conclusions: Our conclusion is that the hypothesized imperfection in screening sensitivity, systematic error, and over-diagnosis do not in themselves explain the observed trial results. Model fit improvement achieved by accounting for population heterogeneity suggests a higher risk of cancer incidence in the intervention group as compared with the control group. [ABSTRACT FROM AUTHOR]