Evidence for Action (E4A), a signature program of the Robert Wood Johnson Foundation, funds investigator-initiated research on the impacts of social programs and policies on population health and health inequities. Across thousands of letters of intent and full proposals E4A has received since 2015, one of the most common methodological challenges faced by applicants is selecting realistic effect sizes to inform calculations of power, sample size, and minimum detectable effect (MDE). E4A prioritizes health studies that are both (1) adequately powered to detect effect sizes that may reasonably be expected for the given intervention and (2) likely to achieve intervention effects sizes that, if demonstrated, correspond to actionable evidence for population health stakeholders. However, little guidance exists to inform the selection of effect sizes for population health research proposals. We draw on examples of five rigorously evaluated population health interventions. These examples illustrate considerations for selecting realistic and actionable effect sizes as inputs to calculations of power, sample size and MDE for research proposals to study population health interventions. https://www.selleckchem.com/products/mpi-0479605.html We show that plausible effects sizes for population health interventions may be smaller than commonly cited guidelines suggest. Effect sizes achieved with population health interventions depend on the characteristics of the intervention, the target population, and the outcomes studied. Population health impact depends on the proportion of the population receiving the intervention. When adequately powered, even studies of interventions with small effect sizes can offer valuable evidence to inform population health if such interventions can be implemented broadly. Demonstrating the effectiveness of such interventions, however, requires large sample sizes.Work contributes to health and health inequity in complex ways. The traditional exposure-disease framework used in occupational health research is not equipped to address societal contexts in which work is embedded. The political economy approach to public health directly examines macro-level societal contexts, but the attention to work in this literature is mostly on unemployment. As a result, we have limited understanding of work as a social determinant of health and health inequity. To fill this gap, we propose a conceptual framework that facilitates research on work, health, and health equity in institutional contexts. As an illustration of different social institutions creating different work-related health, we present characteristics of work and health in the United States and the European Union using the 2015 Working Conditions Surveys data. The results also highlight limitations of the traditional exposure-disease approach used in occupational health research. Applying the proposed framework, we discuss how work and health could be investigated from a broader perspective that involves multiple social institutions and the sociopolitical values that underpin them. Such investigations would inform policy interventions that are congruent with existing social institutions and thus have the potential for being adopted and effective. Further, we clarify the role of research in generating knowledge that would contribute to institutional change in support of population health and health equity.
Respiratory cancers, including lung, tracheal and bronchus cancers, are a leading cause of cancer-related mortality in Israel; however, incidence can differ among demographic groups. Despite the importance of sociodemographic characteristics and the interactions between them to incidence and mortality, this topic is understudied. This study analyzes sociodemographic disparities by sex and ethnicity among Jews and Arabs to understand cancer outcome differences stratified by SES, marital status, and number of children as potential contextual factors.

This retrospective cohort study analyzed respiratory cancer-related mortality rates among Israelis born between 1940 and 1960 over 21-years. The follow up period was between January 1, 1996 and 12.31.2016. Mortality rates for Jews and Arabs were calculated. Using a Cox Regression, a multivariate model was constructed to determine the association between ethnicity and respiratory cancer mortality. The study population was then divided into four groups, by sex an Cancer outcomes among these groups should also be studied separately, by sex, to better understand them.
This study highlights the importance and implications of understanding differences in respiratory cancer mortality between Jews and Arabs, a minority group in Israel, and is relevant for minority groups in general. There is a need to tailor interventions for these groups, based on differing underlying causes and contextual factors for these cancers. Cancer outcomes among these groups should also be studied separately, by sex, to better understand them.While colorectal cancer (CRC) mortality rates have been decreasing, disparities by socioeconomic status (SES) and race/ethnicity persist. CRC screening rates remain suboptimal among low SES and racial/ethnic minority populations, despite the availability of multiple screening modalities. Understanding awareness, knowledge, and utilization of common screening modalities within different racial/ethnic and SES groups is critical to inform efforts to improve population screening uptake and reduce disparities in CRC-related health outcomes. Through the theoretical lenses of diffusion of innovation and fundamental cause theory, we examined the associations of race/ethnicity and SES with awareness, knowledge, and utilization of three guideline recommended CRC screening strategies among individuals at average risk for CRC. Data were obtained from a survey of a nationally representative panel of US adults conducted in November 2019. The survey was completed by 31.3% of invited panelists (1595 of 5097). Analyses were fities and reduce disparities in CRC-related health outcomes.Non-pharmaceutical interventions have been implemented worldwide to curb the spread of COVID-19. However, the effectiveness of such governmental measures in reducing the mortality burden remains a key question of scientific interest and public debate. In this study, we leverage digital mobility data to assess the effects of reduced human mobility on excess mortality, focusing on regional data in England and Wales between February and August 2020. We estimate a robust association between mobility reductions and lower excess mortality, after adjusting for time trends and regional differences in a mixed-effects regression framework and considering a five-week lag between the two measures. We predict that, in the absence of mobility reductions, the number of excess deaths could have more than doubled in England and Wales during this period, especially in the London area. The study is one of the first attempts to quantify the effects of mobility reductions on excess mortality during the COVID-19 pandemic.