Milbank Quarterly最新文献

Policy Points The structural determinants of health are 1) the written and unwritten rules that create, maintain, or eliminate durable and hierarchical patterns of advantage among socially constructed groups in the conditions that affect health, and 2) the manifestation of power relations in that people and groups with more power based on current social structures work-implicitly and explicitly-to maintain their advantage by reinforcing or modifying these rules. This theoretically grounded definition of structural determinants can support a shared analysis of the root causes of health inequities and an embrace of public health's role in shifting power relations and engaging politically, especially in its policy work. Shifting the balance of power relations between socially constructed groups differentiates interventions in the structural determinants of health from those in the social determinants of health.

Policy Points White evangelical theology has an "antistructural" component. Counties with a high percentage of White evangelicals have higher mortality rates and more persons with fair/poor health. The potential influence of antistructural components in evangelical theology on decision making and resource allocation and, ultimately, the length and quality of life of community members presents a point of intervention for religious leaders and policymakers to improve population health.

Context: Structural factors are important determinants of health. Because antistructuralism has been identified as a tenet of White evangelical theology, we explored if there is an association of the percentage of White evangelicals in a US county with two county health outcomes: premature mortality and percentage of fair/poor health.

Methods: Regression analysis was performed with data from 2022 County Health Rankings and the American Value Atlas from the Public Religion Research Institute.

Findings: Every percent of evangelicals in a county is associated with 4.01 more premature deaths per 100,000 population and 0.13% fair/poor health. After controlling for income, education, political ideology, and county school funding adequacy (a proxy for antistructuralism), the associations remain positive and significant.

Conclusions: We hope these findings could inform dialogue and critical analysis among individuals of evangelical faith, particularly fundamental and Pentecostal subsets, regarding a belief system that is inclusive of individual dimensions and health-promoting structural policies like school funding, Medicaid expansion, and antipoverty programs. These findings also demonstrate the importance of considering cultural factors like religion and political ideology in population health outcomes research.

Policy Points Current medical device regulatory frameworks date back half a century and are ill suited for the next generation of medical devices that involve a significant software component. Existing Food and Drug Administration efforts are insufficient because of a lack of statutory authority, whereas international examples offer lessons for improving and harmonizing domestic medical device regulatory policy. A voluntary alternative pathway built upon two-stage review with individual component review followed by holistic review for integrated devices would provide regulators with new tools to address a changing medical device marketplace.

Policy Points Faced with urgent threats to human health and well-being such as climate change, calls among the academic community are getting louder to contribute more effectively to the implementation of the evidence generated by our research into public policy. As interest in knowledge translation (KT) surges, so have a number of anxieties about the field's shortcomings. Our paper is motivated by a call in the literature to render useful advice for those beginning in KT on how to advance impact at a policy level. By integrating knowledge from fields such as political science, moral psychology, and marketing, we suggest that thinking and acting like marketers, lobbyists, movements, and political scientists would help us advance on the quest to bridge the chasm between evidence and policy.

Policy Points People with disabilities experience a vicious cycle of poverty, poor health, and marginalization partly because of the inequitable implementation and enforcement of laws, including underenforcement of civil rights and housing laws and overenforcement of punitive nuisance and criminal laws. Inequitable enforcement reflects policy choices that prioritize powerful entities (e.g., landlords, developers) to the detriment of people who experience intersectional structural discrimination based on, for example, race, disability, and income. Equitable enforcement, a process of ensuring compliance with the law while considering and minimizing harms to marginalized people, can promote health and disability justice by increasing access to safe, stable, and accessible housing.

Policy Points Promoting healthy public policies is a national priority, but state policy adoption is driven by a complex set of internal and external factors. This study employs new social network methods to identify underlying connections among states and to predict the likelihood of new firearm-related policy adoption given changes to this interstate network. This approach could be used to assess the likelihood that a given state will adopt a specific new firearm-related law and to identify points of influence that could either inhibit or promote wider diffusion of specific laws.

Context: US states are largely responsible for the regulation of firearms within their borders. Each state has developed a different legal environment with regard to firearms based on different values and beliefs of citizens, legislators, governors, and other stakeholders. Predicting the types of firearm laws that states may adopt is therefore challenging.

Methods: We propose a parsimonious model for this complex process and provide credible predictions of state firearm laws by estimating the likelihood they will be passed in the future. We employ a temporal exponential-family random graph model to capture the bipartite state law-state network data over time, allowing for complex interdependencies and their temporal evolution. Using data on all state firearm laws over the period 1979-2020, we estimate these models' parameters while controlling for factors associated with firearm law adoption, including internal and external state characteristics. Predictions of future firearm law passage are then calculated based on a number of scenarios to assess the effects of a given type of firearm law being passed in the future by a given state.

Findings: Results show that a set of internal state factors are important predictors of firearm law adoption, but the actions of neighboring states may be just as important. Analysis of scenarios provide insights into the mechanics of how adoption of laws by specific states (or groups of states) may perturb the rest of the network structure and alter the likelihood that new laws would become more (or less) likely to continue to diffuse to other states.

Conclusions: The methods used here outperform standard approaches for policy diffusion studies and afford predictions that are superior to those of an ensemble of machine learning tools. The proposed framework could have applications for the study of policy diffusion in other domains.

Policy Points Government and civil society should be held more accountable for creating food and beverage regulatory policies rather than assigning moral agency to the food and beverage industry. Nutrition policymaking institutions should ensure civil society's ability to design regulatory policy. Government policymaking institutions should be isolated from industry interference.